Example · PhD, Physical Sciences and Engineering
Your fitting script is cheap now. The sample, the instrument and your name on the claim are what employers still pay a PhD for.
29 of your 40 hours still need you
- 21 stay yours
- 8 faster with AI
- 11 tools could take
A typical week at the middle pace. Your plan uses your own tasks.
Is a physics or engineering PhD worth it with AI?
In the work a physical sciences PhD student is heading toward, 29 of a typical 40-hour week still need a person, by our task-by-task count. Tools could already take about 11 hours. Funding, visas and the faculty market will shape your next three years more than any model. AI changes something narrower.
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The code, the first-draft analysis and the literature review in your week are getting cheap, while the bench, the instrument and the judgment about which measurement to run next still need you. In a lab-heavy program, about half of a week is work that holds up.
So the plan does two things. It turns the hands-on work you already do into evidence an employer can see. And it makes you the person who checks the model's output, which is a skill labs and companies are short on right now. Neither move asks you to leave your field or become an AI researcher. If your PhD is fully computational, read the last section first, because your numbers are different.
The hard truth
Academic jobs pay about half what industry pays.
Their academic starting pay is the lowest of any field NSF reports. Staying in academia is a real financial choice.
Sources (1)
- In 2024, new physical science PhDs expected a median $65,140 in academia and $65,000 in postdocs, versus $120,000 in industry. NSF NCSES, Survey of Earned Doctorates, 2026-02
What stays yours
Growing films, synthesizing samples, cleanroom and bench work
This takes presence. Someone has to be in the room with the sample. Self-driving labs exist, and they still need people to judge whether a result is real. When outside researchers re-examined an autonomous lab's 43 claimed new materials, they concluded "no new materials have been discovered in that work" (Leeman et al., PRX Energy, January 2024).
Keeping an instrument running, and knowing its habits
This takes context and presence. O*NET lists maintaining laboratory instruments and troubleshooting malfunctions as a core chemist task. An instrument's quirks are written down nowhere except the log of the person who keeps it alive.
Deciding what to measure next
This rests on context. Experiment design depends on what failed last month, what the tool can actually do and what your PI will fund. A model can list options, but it does not know your lab.
Lab safety and the chemical hygiene plan
Your lab hands you this responsibility. OSHA's lab standard requires "Designation of personnel responsible for implementation of the Chemical Hygiene Plan" and training on it (29 CFR 1910.1450).
Standing behind a result in front of a committee, a referee or a design review
You hold this accountability. Your name is on the paper and the thesis, and you answer the question "how do you know?"
What careers come after a physical sciences PhD?
Plan A is your best move in the field you are studying for. Most sessions in the 13-week plan build toward it.
- A
Aim for industry R&D jobs in chips, batteries or aerospace materials
Why it fits
Why you. If you run a deposition, synthesis or characterization tool now, those skills transfer straight into semiconductor process, integration and metrology, battery and energy materials, or aerospace materials and testing.
The gap. You don't yet have an industry internship or a written record of instrument ownership.
The trade-off. Industry hiring runs in cycles. Some aerospace and defense roles require "U.S. person" status under ITAR, the US arms export rules, which covers citizens, lawful permanent residents and certain protected individuals (22 CFR 120.62), or a security clearance, which is generally limited to US citizens (Executive Order 12968, section 3.1(b)). Pay varies by sector and region.
Other moves that fit
These are also good bets in this field. Read them if Plan A doesn't suit you.
Do 3 to 12 months of thesis research at a national lab
Why it fits
Why you. If you have passed candidacy and your topic sits in a DOE (Department of Energy) science program, the lab is a door you can apply to this fall.
The gap. You need an application to SCGSR, DOE's program that funds PhD research at a national lab, due November 4, 2026 at 5 p.m. ET. You also need a lab scientist who agrees to host you, and proof of candidacy.
The trade-off. This move is the most exposed to federal budgets. SCGSR requires US citizenship or permanent residency. DOE vets foreign nationals at its labs, and the FY2025 NDAA restricts citizens of China, Russia, North Korea and Iran from non-public areas of certain NNSA facilities (DOE testimony, July 15, 2026). Weapons labs often require a clearance.
Keep a coding job open as a backup: data science, scientific software or quant research
Why it fits
Why you. You already write the analysis code, and some students enjoy it most.
The gap. You need a portfolio that shows checking as well as coding.
The trade-off. You compete with people whose whole training is computational. Quant pay is high and hiring is narrow. Do not let this move eat into the industry R&D move.
What's a plan B for physics PhDs?
Plan B is a job AI is creating that these skills already fit. One session a week in the plan trains you for it, so it is ready if your job shrinks or you want a change.
BPlan B, picked for this role
Expert AI trainer (contract)
Standing behind a result in front of a referee trains the exact rigor platforms want when grading AI physics and chemistry answers.
Other options
LLM evaluation data scientist
Your fitting scripts and instrument data work are a natural start on the computational exit toward evaluating AI models.
AI policy analyst
National labs and fellowships need scientists who can explain AI's limits, and deciding what to measure next is that kind of judgment.
In your own plan you can switch to any of the 47 roles.
The first two weeks
The first 2 of 13 weeks. Most weeks have three sessions of 30, 45 and 90 minutes, plus one 40-minute Plan B session (45 minutes in week 4). The plan assumes a mid-October start, so weeks 9 and 10 land on finals and grading with one session plus the Plan B session, and weeks 11 to 13 land on winter break. Weeks 3 and 4 hold two real deadlines, NDSEG on October 30 and SCGSR on November 4, so submit early in the week. SCGSR needs a lab scientist to agree to host you, and if three weeks is too tight, aim for the next round. By week 13 you'll have an SCGSR or NDSEG application submitted, a methods note comparing a model with your own measurements, and ten internship applications sent.
- Week 1: See where your time goes
What you do
- AList a typical week of your research, classes and any teaching. Mark which parts AI already helps with.
- AAsk your PI, the head of your group, how your position is funded and until when. Write the answer down in one sentence.
- AList every instrument, technique and code you have run, with rough hours for each.
- BTake Anthropic's AI Capabilities and Limitations course. Note where AI is likely to slip on physics or chemistry reasoning.
- Week 2: Check fellowship deadlines
What you do
- ACheck whether you qualify for SCGSR, DOE's program that funds PhD research at a national lab. It needs PhD candidacy and US citizenship or permanent residency. Also check NDSEG, a Defense Department fellowship for US citizens or nationals in their first two years of graduate study with three years left.
- AEmail one national lab scientist whose papers you cite. Ask whether they would host you through SCGSR.
- ADraft your NDSEG essays if you qualify. If not, draft the SCGSR research plan.
- BTake the AI as a learning partner module of Anthropic's AI Fluency for Students. Ask AI to solve three textbook problems you know cold.
Three courses from the plan
Checked 2026-10-13.
- Office of Science Graduate Student Research (SCGSR), 2026 solicitationDOE Office of Science · Stipend up to $3,600 a month; round-trip travel paid
Yes, Weeks 2 to 4.
- NDSEG Fellowship, FY2027Department of Defense · $3,600 a month ($43,200 a year) plus up to $5,000 travel
Only if you are a US citizen in your first two years of graduate study.
- NSF Graduate Research Fellowship (NSF 26-526)NSF · $37,000 stipend; $16,000 a year to the school
No. It is closed after your first year.
Risks beyond AI: highFederal funding and access risk
Graduate positions, postdocs and national lab jobs are paid from federal science budgets. FY2026 held, and the FY2027 request asks for deep cuts again. For international students, visa fees and lab access rules add a second layer that has nothing to do with AI.
Where this could be wrong
- The blend assumes a lab-heavy student. A purely computational or theory student has far more of the week in code, simulation and analysis. Without bench work, less than a third of the week holds up.
- Self-driving labs may move faster than we scored, mainly in powder synthesis and solution chemistry. Thin-film, cleanroom and device work is slower to change. Capability is uncertain here. Lab budgets and institutional policy set the pace.
- The postdoc and sector shares behind the blend come from AIP's report on physics PhDs from the classes of 2015 and 2016, published in 2019. It is the latest full breakdown we found, and the mix may have shifted.
- Funding figures come from AAS, Astrobites and Science News summaries of agency and congressional documents. FY2027 is not final as of October 13, 2026.
Also matched: phd student physics, physics phd, chemistry phd. Research checked 2026-10-13. Page updated .