Mercor
MercorVerified listing
Remote

STEM Researchers - MSc/PhD (Must own MacBook)

50–60/hr
Remote
Posted October 19, 2026
hourly
2 openings
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Listing checked October 19, 2026 · pay as published by Mercor

Overview

Mercor connects MSc and PhD researchers in STEM fields with a leading AI lab that needs help benchmarking and improving its models. You will run genuine research workflows on your own Mac, from literature review to data analysis to modeling, and narrate your reasoning as you go. That narration becomes training data for advanced AI systems. Expect roughly 10-20 hours per week with a structured task list rather than the pressure of an internship or consulting gig. Python, MATLAB, and LaTeX show up often, so comfort with a research toolkit matters more than any single language.

What You'll Do6

  • 1Carry out real research tasks end to end on your own Mac, covering literature review, data analysis, modeling, and technical writing
  • 2Talk through your reasoning out loud or in writing while you work so reviewers can follow each decision
  • 3Pull information from varied sources and condense it into clear, accurate summaries
  • 4Turn completed research into well-documented outputs that serve as training material for AI models
  • 5Review your own analysis for errors and correct the record before submitting
  • 6Meet a steady weekly cadence of roughly 10-20 hours and flag blockers early

Requirements6

  • 1Own a MacBook or Mac with an Apple M-series chip or Intel processor, running macOS 15 or later. No Mac means no eligibility
  • 2Currently enrolled in or finished an MSc or PhD in a STEM discipline such as physics, chemistry, biology, mathematics, computer science, or engineering
  • 3Record of hands-on research using tools like Python and Jupyter, MATLAB, R, LaTeX, reference managers, or lab and data analysis software
  • 4Skill at online research: finding credible sources, judging their quality, and summarizing findings without losing accuracy
  • 5Ability to explain your thinking in plain language while you work
  • 6Strong written and verbal communication in English

Who Should Apply

Graduate-level researchers in physics, chemistry, biology, math, CS, or engineering who already own a qualifying Mac and can commit 10-20 hours each week. Candidates who document their reasoning well and move between Python, MATLAB, R, or LaTeX without friction will settle in fastest.

Salary Insight

The role pays $50.00 to $60.00 per hour. That range sits at the upper end for part-time research support work and typically matches candidates with graduate-level training and a working research toolkit. Hours are part-time, so total weekly earnings scale with the 10-20 hour commitment.

Pay and demand for Machine Learning & AI roles

Aggregated

Typical pay

$80/hour

This role

$50–$60/hr

Most Machine Learning & AI roles pay $55–$105 per hour. This role's pay falls inside that range.

Based on 517 similar roles that publish pay · 94 publish only a top rate; those count at the rate they gave

Typical rangeMedian payThis role

Rates shown per hour. Yearly and monthly pay converted; one-time fees and non-USD pay are not included.

Live similar roles
603
Listed in last 30 days
268
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Hiring most right now: micro1 (236) · Mercor (82) · AfterQuery (74)

Most requested skills · share of roles

  • python
    20%
  • technical writing
    11%
  • ai evaluation
    9%
  • model evaluation
    8%

Figures from Machine Learning & AI roles live on NearSkill when this page loaded. A role can close before you apply, so check the listing itself.

Compare your resume against these roles

Location

Typeremote
LocationRemote
This is a remote position

Compensation

$50–60/hr

Required Skills

pythonjupytermatlabrlatexdata analysisliterature reviewtechnical writingstatistical modelingresearch methodologyreference managementmacosinformation synthesisscientific computing

Application Tip

State your Mac model and macOS version near the top of your resume, since candidates without a qualifying Mac get filtered out. Then list two or three concrete research projects and name the exact tools you used on each, such as Python with Jupyter for analysis or LaTeX for write-up, plus any published or submitted output.

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