EXPOSED
This is a catch-all bucket (materials and surface scientists, oceanographic and atmospheric specialists, forensic and government lab scientists), and the modal worker splits time between instrument-based lab or field measurement and desk work: literature review, data reduction, statistical modeling, and report and grant writing. The desk half is the most automatable part of the job — AI already drafts methods sections, writes analysis scripts, and screens literature faster than a postdoc. What holds is hands-on experimental design, running and calibrating physical instruments, field sampling, and being the person who signs off on whether a result is real.
Mixed — a routine tier and a judgment tier. Sample prep, XPS or SEM runs, instrument calibration and drift checks, and deciding which follow-up experiment actually discriminates between two hypotheses stay with you — but the literature triage, the Python that reduces your spectra, the statistics, and the first draft of the methods and results sections are now hours of assisted work rather than days, and those pieces are close to half of a typical week, which is what lands this at 11 instead of the 15+ a bench-only role would earn.
Some physical or field component. Cruise-based water sampling, radiosonde launches, contaminated-site fieldwork and glovebox or vacuum-chamber work put real hands-on hours in the job, but the modal person in this bucket does that in a temperature-controlled lab or on scheduled campaigns, not daily in uncontrolled conditions — a 9 reflects field-and-bench work that is intermittent and mostly staged, unlike a well-site geologist who is outdoors by default.
No licence, no signature requirement. There is no licence to practise as a materials or atmospheric scientist: a PhD and a lab safety certification get you to the bench, and when a result is wrong the institution, the PI, or the accrediting body (ISO 17025, ASCLD for forensic labs) absorbs it — the 3 rather than 0 is only because forensic examiners can be cross-examined personally on their own findings.
Some relationship component. Peer review is blind and papers are read for the data, not the author, so most output travels without you attached; the 7 comes from the parts that don't — program managers who fund you again because your last deliverable was clean, and the internal client who brings a failure analysis to you specifically because you told them the truth about the last one.
Meaningful discretion. Calling a peak real versus instrument artifact, deciding a contaminated run gets discarded rather than reported, and setting detection limits and uncertainty bounds are genuinely yours and often unfalsifiable in the short term — but much of the work runs on written protocols, SOPs and validated methods, and the consequential calls usually go up to a PI, program office, or lab director before anyone acts, which caps this at 12.
Surveyors SAFE
Has AI actually changed your work?