Career Profile

Carol Meyers | Mathematician

Carol Meyers | Mathematician

_0000s_0012_Meyers_Carol.jpg


Lawrence Livermore National Laboratory
Livermore, California

Department: Computational Engineering Division
Education: B.A., Mathematics, 2000, Pomona College; Ph.D. Operations Research, 2006, Massachusetts Institute of Technology
Career stage: Mid–17 years post Bachelor’s

What She Does
National labs serve a role between academia and industry, solving problems too large and/or too applied for academia, and insufficiently profit-driven for industry. Lawrence Livermore National Lab strengthens national security by developing science and engineering solutions to problems in defense, counterterrorism, and weapons/nonproliferation. The areas in which Carol has worked include: energy grid modernization, nuclear counterterrorism, cyber security, stockpile stewardship, and supercomputing. She loves the diversity of the work and feeling like she is always learning. In a typical day Carol usually has a mix of several team meetings and individual work.

Necessary Job Skills
Carol’s mathematical background is in optimization and she is often brought in as a consultant offering mathematical modeling expertise. This usually involves working with teams of other scientists, including engineers, physicists, and computer scientists, and often in collaboration with other national labs and academia.

Work/Life Balance
National lab employees are encouraged to pursue a reasonable work-life balance. Carol has two young kids and she is co-chair of the new moms’ group at her workplace, which has provided her with a great group of co-worker friends for support.

We have a lab-affiliated daycare, which is fantastic, and I am not at all ashamed to say that I enthusiastically network through daycare.

Career Path
Carol knew as an undergrad that she liked proofs and pure math, but she also really wanted to solve real-world problems. She applied to “way too many” grad schools in three different fields, eventually choosing operations research in the hopes it would allow her to do both things—fortunately, this was true! The national labs were a great fit for Carol because they have a blend of research and applications, and she finds working on problems in the “national interest” very motivating.

Career Expectations and Advice
“Networking can be as simple as being friendly and engaging with people on a personal level.”
Networking doesn’t have to be about starting up technical discussions with strangers. Networking can be as simple as being friendly and engaging with people on a personal level—in fact it is often a lot more effective that way. On a related note, working hard does not lead to career growth on its own—the best way to find new opportunities is for people to know who you are and what you do (so don’t skip those department socials).

Salary
According the Bureau for Labor Statistics, the median annual wages for operations researchers working for the federal government is $108,500, across all degree types. A Ph.D. in the field can expect to earn substantially more.

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Carol Meyers | Mathematician

_0000s_0012_Meyers_Carol.jpg


Lawrence Livermore National Laboratory
Livermore, California

Department: Computational Engineering Division
Education: B.A., Mathematics, 2000, Pomona College; Ph.D. Operations Research, 2006, Massachusetts Institute of Technology
Career stage: Mid–17 years post Bachelor’s

What She Does
National labs serve a role between academia and industry, solving problems too large and/or too applied for academia, and insufficiently profit-driven for industry. Lawrence Livermore National Lab strengthens national security by developing science and engineering solutions to problems in defense, counterterrorism, and weapons/nonproliferation. The areas in which Carol has worked include: energy grid modernization, nuclear counterterrorism, cyber security, stockpile stewardship, and supercomputing. She loves the diversity of the work and feeling like she is always learning. In a typical day Carol usually has a mix of several team meetings and individual work.

Necessary Job Skills
Carol’s mathematical background is in optimization and she is often brought in as a consultant offering mathematical modeling expertise. This usually involves working with teams of other scientists, including engineers, physicists, and computer scientists, and often in collaboration with other national labs and academia.

Work/Life Balance
National lab employees are encouraged to pursue a reasonable work-life balance. Carol has two young kids and she is co-chair of the new moms’ group at her workplace, which has provided her with a great group of co-worker friends for support.

We have a lab-affiliated daycare, which is fantastic, and I am not at all ashamed to say that I enthusiastically network through daycare.

Career Path
Carol knew as an undergrad that she liked proofs and pure math, but she also really wanted to solve real-world problems. She applied to “way too many” grad schools in three different fields, eventually choosing operations research in the hopes it would allow her to do both things—fortunately, this was true! The national labs were a great fit for Carol because they have a blend of research and applications, and she finds working on problems in the “national interest” very motivating.

Career Expectations and Advice
“Networking can be as simple as being friendly and engaging with people on a personal level.”
Networking doesn’t have to be about starting up technical discussions with strangers. Networking can be as simple as being friendly and engaging with people on a personal level—in fact it is often a lot more effective that way. On a related note, working hard does not lead to career growth on its own—the best way to find new opportunities is for people to know who you are and what you do (so don’t skip those department socials).

Salary
According the Bureau for Labor Statistics, the median annual wages for operations researchers working for the federal government is $108,500, across all degree types. A Ph.D. in the field can expect to earn substantially more.

Back to List