math phd in industry

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Is a pure math PhD worth anything in industry?

Note: This question is about pure math PhDs and not applied, and I mean pure as in an area of math which has no current applications outside of mathematics. It could also be broadened to theoretical PhDs, but I will focus it.

I'm a recently graduated mathematics major with CS skills and working in software engineering and set to enroll in a good math PhD program this Fall. Since I can either continue working or go to a PhD program, I am naturally asking the question:

What value does a pure math PhD hold in a job application to an applied industry, and why? Admittedly, I cannot see why anyone involved in hiring employees would choose a job applicant with a pure math PhD and zero relevant skills/experience over a job applicant with years of relevant skills/experience or with a degree in a more relevant field.

If this question needs to be more specific I would like to focus on software engineering in the U.S. (still broad, let me know if I must focus it more). But I would welcome answers from any other industries too. This answers a larger question of mine that I have on whether a math PhD is a practical ideal these days, which I started here on Math Overflow .

(Why this is an important question:

• Most (somewhere near 90%, see here , here ) math PhD students will end up industry. Many aim unrealistically for academia, struggle financially with postdocs for a few years, and then eventually switch to industry, usually in finance or software engineering.
• A pure math PhD (or any theoretical PhD) requires years of intense focus on books and papers, and there is not much time for developing industry skills in case they must go to industry. In one case, I saw that a pure math PhD graduate had to get a masters in computer science after their math PhD. Overall, it seems like such students will be in a suboptimal position after graduation in the 90% chance they must go to industry, and that this is all glossed over in academia. Hence, this question could help.)
• software-industry
• career-development
• applications
• career-switch

• 1 I feel like you answered your own question: "I cannot see why anyone involved in hiring employees would choose a job applicant with a pure math PhD and zero relevant skills/experience over a job applicant with years of relevant skills/experience or with a degree in a more relevant field". What more do you want than this? –  Ertai87 Commented Jul 5, 2021 at 19:00
• 2 if you can work in a quant, you're all set. –  Fattie Commented Jul 5, 2021 at 22:37
• @Fattie, I agree with you that the "quantitative field" is opened widely to many smart Ph.D people with some basic computer programming skills. I have seen that many times. –  Job_September_2020 Commented Jul 6, 2021 at 2:46
• There are certainly some places that value mathematical ability and PhD-level thinking. But for the majority of industry positions, a PhD on your resume will signal "overqualified and probably slightly out of touch with the real world". –  B. Ithica Commented Jul 6, 2021 at 9:50
• 1 Buddy of mine ended up as a quant for some investment fund. Pay is top notch but you need to write code too sometimes. Had pure math degree followed by CS degree, followed by CS master and a bunch of coding experience in between. The coding was enough to get him through the door, but his math skills landed him the job. The guy is really passionate about math tho. –  BoboDarph Commented Jul 7, 2021 at 7:19

5 Answers 5

A PhD in the UK now has strong emphasis on employability outside academia, as we have so many PhDs and nowhere near as many faculty positions. What you, and your potential future employers will be wanting are "transferable skills". For example, giving presentations, independent working, teaching others, writing, ability to learn quickly, networking. Maybe investigate the training available as part of the PhD programs you are interested in, to see how much of an emphasis there is on transferable skills.

Admittedly, I cannot see why anyone involved in hiring employees would choose a job applicant with a pure math PhD and zero relevant skills/experience over a job applicant with years of relevant skills/experience or with a degree in a more relevant field.

Industry won't consider a PhD as equivalent to years of experience. So far as they are concerned, it's a higher degree. So you would be treated as a new graduate with a better degree.

They hire new grads, rather than people with years of experience because they are cheaper.

Industry is also not obsessed with exactly what degree you have. Just make sure you aren't either. Instead, they are looking for the right person for the job they have. Which is a lot more than what degree you have.

• This is true: I'm a pharmacist and I work in a completely unrelated field (precision machining). They absolutely didn't care that I have no degree in Engineering - btw it comes pretty handy sometimes as part of my job is coaching Problem Solving - making experts explain the issue to a layperson helps them figure out the solution –  Juliana Karasawa Souza Commented Jul 8, 2021 at 9:25

What I would recommend is looking at the websites of the programs, and seeing where their grads end up. Find out how many graduated each year, and how many got what sort of job.

As you do this, you should assume that anybody they don't mention did not get a decent job, or the program would be happy to list them.

Also, get a count of entries into the program. Somebody once said that there are two types of Ph.D programs, those which admit a few people each year, and graduate a fiew, and those which admit a lot of people and graduate a few. In my experience (and that of a friend who was successful in geting a Ph.D.), you'll have a 30% chance of getting your Ph.D.

You seem to be implicitly assuming that 'industy experience' is a single monolithic thing and if you gained it in any company it will be just as useful in any company. This is certainly not the case. No new hire ever has all the skills a company needs right from the start.

So if a company compares different candidates for a given position they need to look at two components: first how much of the skills needed does the candidate already have and second how fast can they learn the skills they don't yet have. Pure math PhDs tend to do very good on the second component. That is you hire a pure math PhD if you need someone who can learn (and then apply) anything, especially anything vaguely math related, very quickly.

If you job description requires applying the same skills over and over again and do it very well, a math PhD who doesn't have this skill is probably a poor choice. If your job requires finding the needed skills and then learning them over and over again, a math PhD might be a very good choice.

I dare saying this question is so broad there is only one answer: yes. Sometimes.

You assume a pure math PHD has zero application in pretty much every aspect. I am not sure I would buy that given that data analysis and ai work are getting more dominant in many industries, and i.e. a very statistical phd may be quite relevant. There is such a thing as insurance math, which is heavily statistics based. Risk management in the financial field is another area - the necessary domain knowledge may be faster to get than the mathematical knowledge, which the PHD proves.

So, while a "no" is a likely answer for most positions - there are some that are quite specific and extremely math heavy.

That said, as a career - those positions are quite rare, so, "beware what you wish for".

• 1 those are all applied math/stat positions. A Ph.D. in those would be great, but the question is about applied math Ph.D.'s –  Barry DeCicco Commented Jul 5, 2021 at 19:37
• I think you limit that too much. Those are all applied positions, right - but who do you expect to hire anyone and pay him without any application at all? That would literally be a grant. Maybe some billionaire having a "pet mathematician" on staff. Anything else - a pure math PHD may be it, but the position will have applicability or it has no value generated. And you did not ask for pure math jobs, but about HIRING a pure math PHD. In the positions I see, someone would be hired - for a junior/trainee program. –  TomTom Commented Jul 5, 2021 at 19:53
• And especially the statistical field has quite some applications where people actually do publish research papers about things like risk management. So, I could see someone having exposure to this application of statistics in university, then doing a PHD, then doing some move into the industry and being preferred to someone with experience BECAUSE OF HIS PUBLISHED WORK. –  TomTom Commented Jul 5, 2021 at 19:55
• 2 " In the positions I see, someone would be hired - for a junior/trainee program." I agree, which makes getting a pure math Ph.D. less worthwhile, especially since an employer could always go after people with applied BS degrees. As for your original post, I'm reasonably aware of the situation; I was in a biostat Ph.D. program for a while, and talked with many stat people (we were taking the same courses). A pure math Ph.D. is not a statistics degree. –  Barry DeCicco Commented Jul 5, 2021 at 22:22
• 1 It's interesting how everyone here seems to think that PhD is essentially trade school. –  ojs Commented Jul 6, 2021 at 9:14

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PhD in Applied Mathematics

Phd in applied mathematics degree.

Applied Mathematics at the Harvard John A. Paulson School of Engineering is an interdisciplinary field that focuses on the creation and imaginative use of mathematical concepts to pose and solve problems over the entire gamut of the physical and biomedical sciences and engineering, and increasingly, the social sciences and humanities. The program has focuses on understanding nature through the fusion of Artificial Intelligence, Computing (classical to quantum), and Mathematics. We value foundational contributions, societal impact, and ethics in our work. Our program uniquely interfaces with diverse fields, including physics, neuroscience, materials science, economics, biology and fluid mechanics, to tackle some of the most pressing challenges of our time, such as sustainability, responsible digital transformations, and health and well-being.

Working individually and as part of teams collaborating across the University and beyond, you will partner with faculty to quantitatively describe, predict, design and control phenomena in a range of fields. Projects current and past students have worked on include collaborations with mechanical engineers to uncover some of the fundamental properties of artificial muscle fibers for soft robotics and developing new ways to simulate tens of thousands of bubbles in foamy flows for industrial applications such as food and drug production.

Our core mission is to provide students with individualized programs tailored to their interests, needs, and background. We welcome students from diverse technical backgrounds. Our program is dedicated to the principles of diversity, equity, and inclusion. We celebrate and value differences among our members, and we strive to create an equitable and inclusive environment for people of all backgrounds.

APPLY NOW >

Applied Mathematics PhD Degree

Harvard School of Engineering offers a  Doctor of Philosophy (Ph.D.) degree in Applied Mathematics conferred through the Harvard Kenneth C. Griffin Graduate School of Arts and Sciences . Doctoral students may earn the masters degree en route to the Ph.D. Prospective students apply through Harvard Griffin GSAS; in the online application, select  “Engineering and Applied Sciences” as your program choice and select “PhD Applied Math” in the Area of Study menu.

The Applied Mathematics program does not offer an independent Masters Degree.

Applied Mathematics PhD Career Paths

Our graduates have gone on to careers such as start-up pioneers, social innovators, and a range of careers in industry in organizations like the Kingdom of Morocco, Meta, and Bloomberg. Others have secured faculty positions at Dartmouth, Imperial College in London, and UCLA. More generally, students with a PhD in Applied Mathematics can go on to careers in academia, banking, data science, bioinformatics, management consulting, government/military research, and more. Also, r ead about some of our Applied Mathematics alumni .

Admissions & Academic Requirements

Please review the  admissions requirements and other information  before applying. Our website also provides  admissions guidance ,   program-specific requirements , and a PhD program academic timeline .

Academic Background

Applicants typically have bachelor’s degrees in the natural sciences, mathematics, computer science, or engineering. 

Standardized Tests

GRE General: Not Accepted

Applied Mathematics Faculty & Research Areas

View a list of our  Applied Mathematics faculty and applied mathematics  affiliated research areas , Please note that faculty members listed as “Affiliates" or "Lecturers" cannot serve as the primary research advisor.  

Applied Mathematics Centers & Initiatives

View a list of the research centers & initiatives at SEAS and the Applied Mathematics faculty engagement with these entities .

Graduate Student Clubs

Graduate student clubs and organizations bring students together to share topics of mutual interest. These clubs often serve as an important adjunct to course work by sponsoring social events and lectures. Graduate student clubs are supported by the Harvard Kenneth C. Griffin School of Arts and Sciences. Explore the list of active clubs and organizations .

Funding and Scholarship

Learn more about financial support for PhD students.

• How to Apply

Learn more about how to apply  or review frequently asked questions for prospective graduate students.

In Applied Mathematics

• First-Year Exploration
• Areas of Application
• AM & Economics
• How to Declare
• Who are my Advisors?
• Secondary Field
• Senior Thesis
• Research for Course Credit (AM 91R & AM 99R)
• AB/SM Information
• Peer Concentration Advisors (PCA) Program
• Student Organizations
• PhD Timeline
• PhD Model Program (Course Guidelines)
• Oral Qualifying Examination
• Committee Meetings
• Committee on Higher Degrees
• Research Interest Comparison
• Collaborations
• Cross-Harvard Engagement
• Clubs & Organizations
• Centers & Initiatives
• Alumni Stories

Graduate News

Master's student capstone spotlight: AI-Enabled Information Extraction for Investment Management

Extracting complicated data from long documents

Academics , AI / Machine Learning , Applied Computation , Computer Science , Industry

Master's student capstone spotlight: AI-Assisted Frontline Negotiation

Speeding up document analysis ahead of negotiations

Academics , AI / Machine Learning , Applied Computation , Computer Science

Master's student capstone spotlight: A Remote Sensing Framework for Rail Incident Situational Awareness Drones

Using drones to rapidly assess disaster sites

Advice and Resources for Mathematics Graduate Students

Non-Academic Careers

Graduate school and the post-docs that follow provide great freedom, both personally and academically. The opportunity to earn a living, albeit modest, while earning a PhD is an amazing privilege. Enjoy it, right now! Don’t blow it by stressing about the future.  Heed the wise words of Luis Serrano (UM PhD 2011), whose first job was a post-doc at the University of Quebec, but who has since worked at Google, Udacity and Apple: “ If I had known how easy it is for a math PhD to find a fascinating 6-figure job in an amazing city, I would have worried less and enjoyed my academic career more. ”

The culture of elite Math PhD programs like Michigan often emphasizes preparation for academic careers. And being a professor is a great job. But it is only one of many great jobs for PhD mathematicians .   It is completely reasonable for highly trained mathematicians to seek to live in a particular city, or to want to make a lot of money, or to make an impact on society working on some issue about which they are passionate, such as cancer research or climate change . Michigan math PhDs are in high demand! This is true now more than ever : the data revolution has rendered high-level mathematics and problem solving stamina indispensible in virtually every human endeavor,  including computer vision for a robotic exoskeleton for paralysis patients .

All mathematicians should know something about these twenty-first century applications of mathematics: professors  need to understand the tremendous opportunities for their students and graduate students should be aware of the wide range of meaningful career options for math PhDs. Please check out some of these resources so that you will be informed!

• Our Invitations to Industry Series :  come meet recent Michigan Math PhD alumni to learn about what their careers look like in industry–this will help you better mentor your students, and give you the peace of mind that there are many great jobs for Math PhDs.
• Life after Graduate School , a similar Seminar series  here at Michigan run by the physics department, in which PhD alumni in Physics/Astronomy return to tell current graduate students about what they’re doing now.
• Moving from academic to industry career plans: A personal story , by Mark Greenfield, UM Math PhD 2020, now in finance (Susquehanna) 
• Preparing for a Career Outside the Academy, by Ethan Zell, UM Math PhD 2024
• Industry or Academia? by Zhan Jiang ,  UM Math PhD 2021, now in tech (Google) 
• Five Reasons I chose an industry Career by Gilad Pagi , UM Math PhD 2018, now in tech (Google)
• Why I landed an Industry Job by Yiwang Chen, UM Math PhD 2022, now in tech at Google
• Moving from academia to industry — a mathematician’s tale , by Rami Luisto, now in data science, Math PhD from Helsinki who regularly visited UM as a PhD/post-doc.
• The Erdos Institute:   Michigan Math belongs to this exciting consortium, which introduces current graduate students to PhD alumni in industry, hosts free “ Boot Camps ” to provide students with skills, maintains a Jobs Posting Board on Linked In, and perhaps most importantly, offers a job placement service. All Michigan Math, AIM, and physics PhD students, post-docs and alumni can take advantage of this service by reaching out to Erdos’s Placement coordinator Amanda Perrin or director Roman Holowinsky through Linked In or asking Karen Smith to put you in touch with them. Faculty running PhD programs curious about how to get their own institution involved can also reach out! Here’s a link to some Erdos Institute forms that might be of use.
•   Advice from TPSE about careers outside academia
• Job and internship opportunity postings : if you are ready to look for a job or internship, you’ll want to keep an eye here.
• Linked In is widely used by mathematicians working in industry, and increasingly, by academic mathematicians who collaborate with them. Make a free profile and join our Michigan Math PhD Alumni group !
• The BIG Network  for information about careers for mathematicians and mathematical scientists in Business, Industry, and Government. Their home page has many personal stories from Math PhDs who have transitioned to industry.
• Siemen’s internships .
• Advice from Susan Hermiller  about finding internships
• A compilation of resources for students in Scientific Computing and Mathematical Modeling , from Robert Krasny
• Stanford mathematician Gunnar Carlson ’s AI company, which uses topology to do data analysis. And a blog Carlson wrote on AI and topology.

under construction

PhD in Mathematics

The PhD in Mathematics provides training in mathematics and its applications to a broad range of disciplines and prepares students for careers in academia or industry. It offers students the opportunity to work with faculty on research over a wide range of theoretical and applied topics.

Degree Requirements

The requirements for obtaining an PhD in Mathematics can be found on the associated page of the BU Bulletin .

• Courses : The courses mentioned on the BU Bulletin page can be chosen from the graduate courses we offer here . Half may be at the MA 500 level or above, but the rest must be at the MA 700 level or above. Students can also request to use courses from other departments to satisfy some of these requirements. Please contact your advisor for more information about which courses can be used in this way. All courses must be passed with a grade of B- or higher.
• Analysis (examples include MA 711, MA 713, and MA 717)
• PDEs and Dynamical Systems (examples include MA 771, MA 775, and MA 776)
• Algebra and Number Theory (examples include MA 741, MA 742, and MA 743)
• Topology (examples include MA 721, MA 722, and MA 727)
• Geometry (examples include MA 725, MA 731, and MA 745)
• Probability and Stochastic Processes (examples include MA 779, MA 780, and MA 783)
• Applied Mathematics (examples include MA 750, MA 751, and MA 770)
• Comprehensive Examination : This exam has both a written and an oral component. The written component consists of an expository paper of typically fifteen to twenty-five pages on which the student works over a period of a few months under the guidance of the advisor. The topic of the expository paper is chosen by the student in consultation with the advisor. On completion of the paper, the student takes an oral exam given by a three-person committee, one of whom is the student’s advisor. The oral exam consists of a presentation by the student on the expository paper followed by questioning by the committee members. A student who does not pass the MA Comprehensive Examination may make a second attempt, but all students are expected to pass the exam no later than the end of the summer following their second year.
• Oral Qualifying Examination: The topics for the PhD oral qualifying exam correspond to the two semester courses taken by the student from one of the 3 subject areas and one semester course each taken by the student from the other two subject areas. In addition, the exam begins with a presentation by the student on some specialized topic relevant to the proposed thesis research. A student who does not pass the qualifying exam may make a second attempt, but all PhD students are expected to pass the exam no later than the end of the summer following their third year.
• Dissertation and Final Oral Examination: This follows the GRS General Requirements for the Doctor of Philosophy Degree .

Admissions information can be found on the BU Arts and Sciences PhD Admissions website .

Financial Aid

Our department funds our PhD students through a combination of University fellowships, teaching fellowships, and faculty research grants. More information will be provided to admitted students.

More Information

Please reach out to us directly at [email protected] if you have further questions.

Applied Mathematics MS Program

This is a two-year professional degree program designed to prepare you for a career in contemporary industry or business. You'll receive thorough training in applied mathematics and scientific computing, exposure to mathematics-related subjects in science and engineering, and experience in a group project. Our graduates have been successful in securing desirable positions with companies ranging from small, local firms to large, international corporations.

Professor; Director, Applied Mathematics & Computation; Director, Applied Math MS Graduate Admissions

Program goals and structure

The Master's Degree Program in Applied Mathematics is specially designed to prepare graduates for a successful career in today's industrial/business world. Accordingly, the program is structured into the following three components:

• a core of graduate courses in applied subjects within the Department of Mathematics and Statistics;
• a selection of advanced courses in other departments;
• a group project in which an applied scientific problem is undertaken in a colloborative effort.

The graduate courses in the Department concentrate on Analytical Methods, Numerical Methods, and Probability/Statistics. These courses give the student a thorough background in advanced applied mathematics.

Given the interdisciplinary nature of Applied Math, students are encouraged to take courses outside the Department. These are determined depending on each student's interests and preparation. In recent years, they have been chosen from Computer Science, Engineering (Industrial, Mechanical, Electrical), Physics, and Management Science. These courses expose the student to the use of practical mathematical tools by scientists and engineers. Courses taken outside of the department require the director's approval in order to count towards the MS degree.

Students in the program are required to complete at least one course that includes a group project component. The group projects are intended to emulate industrial teamwork on a large, technical problem. Through the combined efforts and diverse talents of the group members, a mathematical model is developed, a computer code is implemented, and a final report is written. In the process, the students learn how to start solving a new and hard problem, how to make a professional presentation of their work, and how to collaborate effectively with their coworkers.

Applications and admissions

Those wishing to be considered for Fall admission should submit all application materials to the Graduate Admissions Office during the preceding Spring. Reviewing of applications will start after the application deadline  January 10 , with precedence given to those before that date. Later applications are considered provided that openings are available.

All applicants are expected to have a strong undergraduate preparation in mathematics, including advanced calculus, linear algebra, and differential equations. Some exposure to computer science and/or scientific computing is also desirable, as is some knowledge of another area of science or engineering. A Bachelor's Degree in Mathematics, however, is not necessary. Students with undergraduate majors in Physics or Engineering, for instance, and with sufficient mathematical background, are encourage to apply.

The program is able to offer a tuition waiver and a stipend to a limited number of students upon admission. This financial support takes the form of a teaching assistantship in the department. The duties of the students in the Master's Degree Program are usually restricted to grading or consulting for an undergraduate course, although instructing in an elementary course is also possible.

For additional information, contact the Program Director  Markos Katsoulakis .

Recent Applied Math MS Graduates

List under constant construction. Recent alumni of the Applied Math MS program may contact Graduate Program Manager Kaitlyn O'Konis ( @email ) to provide the department with their most recent employment information.

• Dvir Blander (Data Analyst, SmartSense by Digi)
• Nuha Futa (Senior Data Scientist, Citizens)
• Suzet Nkwaya (Data Scientist, MFS Investment Management)
• Linqi Meng (Holyoke Medical Center)
• Matheau Santana-Gijzen (Graduate Student, PhD, Johns Hopkins University)
• Renato Spacek (Graduate Student, PhD, École de Ponts ParisTech, France)
• Nicolas Malloy (System Engineer, Zoox)
• Brendan Shanahan (Senior Software Engineer, Intellia Therapeutics, Inc.)
• Program Overview
• Applied Mathematics MS
• Remote Statistics MS
• How to Apply
• Financial Aid
• Admissions FAQ
• Recent Courses
• Qualifying Exams
• Alumni Testimonials

Award-winning teaching, research opportunities, and interdisciplinary programs in a diverse, inclusive community of excellence.

Lederle Graduate Research Tower, 1654 University of Massachusetts Amherst 710 N. Pleasant Street Amherst, MA 01003-9305, USA

Department Phone: (413) 545-2762 Department Fax: (413) 545-1801 Department Office: LGRT 1622

Graduate Program in Mathematics at University of Arizona

Come study Mathematics at the University of Arizona!

As a student at Arizona, you will get a very well-rounded education suitable for many mathematically oriented careers. Additionally, you will benefit by:

• Financial support for five or six years though research, teaching, and internships.
• A unique Sonoran Desert location in the heart of the historic Southwest.
• a rigorous foundation in core mathematics: algebra, analysis, and geometry-topology
• a second-year research experience (RTGs)
• a variety of research specialties, encompassing the creation, application, and teaching of mathematics.
• A nationally recognized tradition of innovation in teaching and curriculum development
• Ample opportunities for outreach and service.

Please see our poster for more information regarding our program and upcoming Virtual Open House on Wednesday, November 1, 2023 at 10 AM.

Create, Apply, and Teach Mathematics!

At the University of Arizona, through research, teaching and coursework you will will learn, create, teach, and apply mathematics in a variety of settings. You will become part of the Arizona tradition of excellence and innovation.

Research Specialties

Mathematical research at Arizona is carried out by internationally recognized researchers in a wide variety of fields, including Algebra and Geometry, Analysis, Applied Math, Math Education, and Probability and Statistics. All of these groups are strong, but the groups in non-linear waves, mathematics education research, and number theory are particularly well-known. At University of Arizona, you are required to do an early research project (the research tutorial group), a unique part of the UA program.

You can read more about research opportunities here .

Excellence in Teaching

Arizona has long been known for excellence and innovation in teaching undergraduates. As a Teaching Assistant (TA) at Arizona, you will have full responsibility for your class, including lectures, homework and exam preparation, and assignment of grades. You will benefit from an extensive collection of TA training and mentoring resources and you may choose to teach more advanced courses or become involved in outreach programs to local schools. You can read more about teaching opportunities here .

Coursework is offered in most major areas of mathematics, applied mathematics, and statistics. In addition, students are required to take courses from other departments or to have an internship. You can read more about courses here .

More information

Want to learn more about our Graduate Program?

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82 PhD jobs in Mathematics

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• PhD positions in Applied Mathematics (53)
• PhD positions in Statistics (29)
• PhD positions in Computational Mathematics (18)
• PhD positions in Probability Theory (12)
• PhD positions in Analysis (6)
• PhD positions in Stochastics (6)
• PhD positions in Number Theory (5)
• PhD positions in Algebra (4)
• PhD positions in Logic (4)
• PhD positions in Geometry and Topology (4)

Other main fields

• PhD positions in Engineering (274)
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• PhD positions in Agricultural Science (31)

Search results (82)

Vacancy for two PhD researchers in Predictive and Prescriptive Process Modelling

You will work at the LIRIS research group of the Faculty of Economics and Business at KU Leuven. One position is hosted at KU Leuven, with an exchange period at University of Melbourne. The second ...

Doctoral candidates in Statistics and Probability

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Quality control within Injection Moulding exploiting data and physical models (APRIORI DC5)

The KU Leuven Mecha(tro)nic System Dynamics division (LMSD) and the Campus Diepenbeek Polymer Processing & Engineering (PPE) groups are searching for a Doctoral Candidate to join its team to work i...

PhD: AI for data-driven representation optimization for time series

The work will be performed within the research division STADIUS at the Department of Electrical Engineering (ESAT). STADIUS' major research objective is to contribute to the development of improved...

PhD position in Environmental Economics 60%

The Chair of Environmental Economics, under the direction of Prof. Dr. Frank Krysiak, at the Faculty of Business and Economics of the University of Basel invites applications for a PhD position. Fo...

PhD Positions in Cancer Research

Are you looking for excellent research opportunities for your PhD studies at the forefront of cancer research? The German Cancer Research Center (DKFZ) in Heidelberg invites international students holding a Master’s degree in (molecular) biology, ...

Three 2-year Postdoctoral Fellowships at the Zukunftskolleg

(Fulltime, E 13 TV-L)Reference No: 2024/114. The preferred start date is April 1st, 2025. Conditionally on the submission of an external grant, the position can be extended for an additional year. In principle, the position can be divided into two...

PhD position Surrogate modeling and Machine Learning for science and engineering

Last application date Jul 31, 2024 00:00Department TW05 - Department of Information TechnologyContract Limited durationDegree Master’s degree in Computer Science, Mathematics, Engineering, or equivalentOccupancy rate 100%Vacancy type Research staf...

PhD-positions in Finance

The Department of Finance at the University of Luxembourg invites students to apply for PhD-student positions in Finance.Your Role... The program follows the standard international format with rigorous coursework in the first year and for the rema...

PhD student Causal Machine Learning

Last application date Sep 01, 2024 00:00Department WE02 - Department of Applied Mathematics, Computer Science and StatisticsContract Limited durationDegree Master of Statistics, or Master of Mathematics, Physics, Computer Science, Engineering (eac...

Time-scale aware analysis and control of hybrid networked systems

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getting a job with a PhD in (pure) mathematics

Probably this concern has been addressed several times here but I will give a try to get other people's perspective from my situation. I am feeling sort of hopeless these times.

I am in my last year of my PhD in mathematics and doing my dissertation soon, my research was mainly devoted to algebraic topology and I made some progress in my advisor's particular area. However, I faced some problems during my studies (personal issues) and I never built a strong relationship with my advisor; so I could not finish all the initial research proposal intended for my PhD thesis.

I recently had a sincere talk with my advisor about my future, and he said that my progress is worth for a PhD thesis but it is not anything very surprising that is worth publishing, so I will be graduating with zero publications. He said that my chances of getting a PostDoc positions are really low and that I can not expect a strong recommendation letter from him. My advisor has a few collaborators (from overseas mainly) and none in the local department. He also never supervised another Master or PhD student while I was under his supervision, then I never got a chance to network or engage properly with other classmates. My advisor kindly suggested to explore other options in the job-market besides academia.

I like to explore new things, and in my free time during my studies I attended several teaching workshops, seminars and courses (I got a small degree in "university teaching"), and I am also familiar with Python, R, Matlab and Sage; however, I learn those things for fun and I have never really worked in a big project using any of that.

I do not know what to focus on and what kind of job should I look for after I finish my PhD

I would like to keep doing research in Math, but my area is not very popular lately and I feel that I have no chances of succeed getting a PostDoc; I also feel that I do not have (demonstrable) skills to perform a job with "real-life" applications so probably my chances getting there are also low. And I do not really know the Teaching job-market, I think that those positions are temporary and it would be hard to find a place that is willing to sponsor a work visa (I am not a US-citizen, and the job market in the third-world country that I am from is nonexistent for PhD's in this area)

• mathematics
• career-path

• 4 Learn to program. –  The Dude Commented Jan 25, 2021 at 15:51
• 1 Probably much too late for the original poster, but maybe helpful to some others: have you heard of topological data analysis ? Not saying being good at TDA would get you a job on its own, but could be a stepping stone to applied areas if you already know algebraic topology. –  J W Commented Sep 1, 2021 at 14:06

4 Answers 4

Your supervisor is honest, blunt, and very helpful because by ruling out the academic path he's saving you a lot of time.

The bad news is it sounds like you screwed up your PhD. Not getting strong research results, not having diversified your PhD experience (e.g. lack of teaching experience makes it harder for you to get a teaching job), and not having a firm idea of what you want to do after the PhD means you sound lost right now. The good news is, chances are you learned more than you think you did, and those things are applicable to the job market.

First : don't think you have to do research. It is what you've been doing for the PhD, but it's not what you have to do in the future. Just consider this: if you like research + are good at it, why didn't you do better in the PhD? Why weren't you able to complete the initial research proposals, why weren't you able to get publishable results, why weren't you able to impress your supervisor such that he can write a strong letter of recommendation? You might have good reasons for these, and it's up to you to convince yourself that yes, you still want to do research, and yes, you are talented + motivated enough to succeed in it.

If I were you, I'd start examining the possibility that I am not actually good at research and / or it is not what I want to do. Do some serious soul-searching here. You are making a life-altering decision. If it makes you feel bad that by leaving academia you are "failing", don't worry too much about it: there's a good chance that by leaving academia you'll have a more successful life (in terms of material possessions).

Second : go to your local jobs portal (use Google if you don't know what these are) and search for jobs that require a PhD in mathematics. Do you find anything that catches your fancy? For example searching on indeed.com for "phd math", I get this job among many others. Note the requirements:

Preferred qualifications: MBA, Master's or PhD degree in a quantitative field . Experience with stakeholder management and ability to influence senior stakeholders. Demonstrated knowledge of statistics and data analysis including R programming or other statistical software packages.

I highlighted the most relevant parts. You say you are familiar with R. That means you are in business! You can potentially do this job! If you further have experience with statistics and data analysis (do you?) you're in an even better position.

It's up to you to search the jobs portal for jobs you can do, and then it's up to you to apply. It's true that visa issues might sink your candidacy, but it's also true that because PhDs are relatively rare, you might have skills nobody else will have and therefore the employer is willing to sponsor you. You will not know unless you try.

Do remember that even if you can't find a US employer, you can still work elsewhere. It's a big world out there, and it's not true that third-world countries don't need your skills. Example of such a job in India (admittedly they're not looking for PhD-level candidates, but you could still apply).

Third : once you have an idea about what the options in industry are like, then you can start thinking about what you want to do. Are you sure you still want to do math research? If so I'd talk to your supervisor again about what options are available to you. He's already told you your prospects are not good, so you'll need all the help you can get from him. For example, perhaps you could find a position as a teaching assistant somewhere and do research in your spare time. This will not be easy - doing research while holding a full-time job is very difficult - and it's not likely to be well-paid, but if it's what you want to do, you can try.

On the other hand if you think industry will serve you better, then finish up your thesis & defense and start applying for jobs. Be sure to visit your university's career center as well; they'll be able to help you a lot.

This question is a year old, but it matched my own experience enough (including the specialization in algebraic topology) that I felt obliged to comment. Getting an academic math position is a crapshoot under the best of conditions. The field is glutted with other highly competent applicants (pretty much everyone going into pure math does so with the intention of doing pure math research); the field doesn't have the money of, say, computer science; and there really aren't any opportunites to do pure math research outside of academia and maybe a single-digit number of industry labs. With a great publication record and glowing recommendations from well-established professors, you have an outside shot at it. Without them, it's vanishingly likely to happen. It's unfair, especially if you wind up with a useless or abusive advisor, fall into a field that isn't the cool new thing, choose (or get saddled with) a research project in your limited time to prove yourself that doesn't work out, and so on. What's even worse is that (unlike some other fields) there's really no way to burnish your credentials; there's nothing you can do outside of academia that academic mathematicians would care about.

So, unfortunately, there's probably nothing you can do. It should be relatively easy for you to find some job in industry, though; the tricky part is finding one you like. Just being able to think rigorously and scientifically is a prized skill in industry, while it's taken as given in academia. (Conversely, some interpersonal and organizational skills work the opposite way. On the other hand, there are more opportunities to pick up the latter, whereas there's really no place to pick up pure math skills outside academia.) I don't see anything in your post to suggest that you aren't employable, so at least you should have some breathing room to take a look at what's out there and see if there's anything that might be, if not exciting, at least acceptable.

While a position at a top research institution may not be in your immediate future there are things you can do, up to and including proving that your advisor is wrong.

You don't actually need a faculty position to do research or publish in math but, in my experience, you do need a circle of collaborators. You indicate that you don't have that, but it would be good to start to develop it. Attendance at conferences is a good way in computer science, at least. Meet people, speak with them about ideas, and such.

There are also many teaching colleges around the world that value good math teaching over research. Almost all will require some, but many emphasize teaching the next generation over serious research. The MAA, for example, is full of people who, while doing research, focus much of their efforts on teaching.

And, of course, teaching at pre-college level is also open to you. You may find yourself overqualified for this, but it can make a satisfying life if you value teaching.

But, you can put it together if you have the willingness to do so. A lower level position, while developing mathematical ideas within a circle of collaborators can put you on a path to a better position, proving your advisor wrong in the long term if not immediately.

If your advisor is actually inexperienced at this he may be making a mistake in his analysis and also in his general advising. In particular, his assessment that you can't publish what you've done might just be wrong. You won't know unless you try.

Your life is what you make it.

• 9 Unfortunately, the visa issue is a serious one for US jobs. Academic positions at colleges and universities are not subject to the H-1B quota, but pre-college teaching and industry jobs are, and, even if one can get a position, one has less than 50% chance of getting an H-1B and being able to accept the position. –  Alexander Woo Commented Mar 1, 2019 at 21:42
• 2 The OP should be aware of the "Optional Practical Training" program that allows recent graduates in STEM fields to work in the US for a period of time (up to 3 years as I recall) after completing their degrees. Teaching at a community college on OPT is sometimes a viable option for new PhD's who have acquired enough teaching experience to obtain such a position. –  Brian Borchers Commented Mar 2, 2019 at 0:25

I know it's too late but for someone in the future, there are some folks in machine learning / AI (or more generally applied/engineering) community who are interested in the intersection with pure math, e.g., Topological data science employing the concept of Homology from Algebraic topology or homotopy methods in computational aspects of polynomials.

So, considering these directions and finding positions in industry might be interesting! ** In these directions, people likely do not appreciate the advancement in theoretical direction like the way you used to research on though...

• 3 Forks or folks? –  Moishe Kohan Commented Aug 12, 2023 at 17:21
• 1 @MoisheKohan thank you! –  Rowing0914 Commented Aug 12, 2023 at 21:56

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Math MS vs PhD for industry job

• Thread starter Holomorphism
• Start date Jan 25, 2013
• Tags Industry Job Phd
• Jan 25, 2013
• Scientists develop new technique for bespoke optical tweezers
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From the previous advice I've seen on here, it is a bad idea to do a PhD for salary advancement.  

DeadOriginal said: From the previous advice I've seen on here, it is a bad idea to do a PhD for salary advancement.

• Jan 29, 2013

Thank you both for your responses. It sounds like I could go either PhD or MS and still have good options.  

• Feb 5, 2013

As a scientist with experience in both academia and industry, I can offer some insights into your question. First of all, congratulations on being in a position to choose between a Master's and PhD program. Both degrees have their own merits and can lead to successful careers in industry. In terms of job market competitiveness, having a PhD may give you an advantage over candidates with only a Master's degree. This is because a PhD demonstrates a higher level of expertise and specialization in a particular field, which can be attractive to employers. However, having a Master's degree can also make you competitive, especially if you have relevant work experience and skills. In terms of salary, it is possible to earn six figures with a Master's degree in mathematics, especially if you have relevant work experience and skills in programming. However, having a PhD may open up opportunities for higher-paying positions, such as research and development roles or leadership positions. Ultimately, your salary will also depend on the company you work for and the demand for your specific skills in the job market. It is also worth considering the type of work you want to do in industry. If you are interested in applied mathematics and have a specific field in mind, such as mathematical biology or imaging, a PhD may be beneficial as it will allow you to gain more specialized knowledge and skills in that area. However, if you are more interested in programming and software development, a Master's degree may be sufficient for you to enter the industry and gain experience. In summary, there is no right or wrong answer to your question. Both a Master's and PhD can lead to successful careers in industry, and it ultimately depends on your personal goals and interests. I would recommend researching job postings in your desired field and seeing what qualifications and skills are required for the positions you are interested in. This can help you make a more informed decision about whether to continue on to a PhD or stop at a Master's. Good luck with your decision!  

Related to Math MS vs PhD for industry job

What is the difference between a math ms and a math phd for industry jobs.

A Math MS (Master of Science) typically requires 2-3 years of coursework and a research project, while a Math PhD (Doctor of Philosophy) can take 5-7 years and involves more extensive research and a dissertation. In terms of industry jobs, a PhD may be more desirable for research and leadership positions, while an MS may be sufficient for other roles.

Which degree is more marketable for industry jobs?

It depends on the specific industry and job role. Generally, a PhD may be more marketable for research and academia positions, while an MS may be more appropriate for technical and practical roles. However, both degrees can be valuable and marketable depending on the individual's skills and experience.

Do Math MS and PhD graduates have different salary potentials in industry jobs?

Again, it depends on the specific industry and job role. In some industries, a PhD may command a higher salary due to their advanced research and analytical skills. However, in other industries, an MS may have similar salary potential if they possess relevant experience and skills.

Are there any specific job titles or positions that require a Math PhD over an MS?

Yes, some job titles or positions may specifically require a PhD, such as research scientist, data scientist, or professor. These roles typically involve advanced research and analytical skills that are acquired through a PhD program.

What are the potential career paths for Math MS and PhD graduates in industry?

Both Math MS and PhD graduates can pursue a variety of career paths in industry, such as data analyst, actuary, statistician, operations research analyst, and more. With a PhD, graduates may also have opportunities for research and leadership positions in industry or academia.

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Math PhD Programs with Machine Learning (for industry career)

I'm a current rising senior math major in the U.S. and I'm thinking about attending grad school for math (a PhD probably). However, this summer I worked with a professor at a different university on a machine learning problem and I loved it. In fact, I think this is a field that I want to go into. Given my mathematical background, I think that I would like to go to a math PhD program and specialize in some type of machine learning, with the ultimate goal of ending up as a machine learning engineer in the tech industry.

My question is, does anyone know of a good math PhD program in the U.S. that has strong machine learning research and that would prepare me for the industry? Currently I've been thinking about the Tufts math program, where there seems to be some ML research in the HILDA group.

I'd love any advice or wisdom from anyone! Hope everyone is staying safe and healthy!

Also, I'm probably going to repost this to r/math and r/MachineLearning