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Principal Research Scientist (Computer Science / Computational Physics)

micro1Legit · not rated yetPosted 13 days ago

Pay: $100–400/hr

Who can apply
Countries not stated in the listing
Hours
Hours vary · Freelance
Where
Remote, work from home
Job type
Expert (SME) review
Openings
4 openings

At a glance: A freelance, remote expert (SME) review job with micro1. It pays $100–400/hr, with hours that vary. The listing doesn't say which countries can apply.

  • Countries not stated

    The posting doesn't say which countries can apply, so check before you apply. What micro1 says in general: Recruits worldwide apart from residents of 21 countries and regions, among them China, Russia, Ukraine, Iran, Venezuela and Ethiopia; some listings accept applicants from the US, UK or Canada only

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What happens after you click Apply

  1. You leave AI Trainer HQ and go to micro1’s own site.
  2. Pick a role, apply and answer the screening questions attached to it
  3. Sit the AI interview with Zara, spoken and recorded, about 20–40 minutes
  4. Complete a technical assessment if the role has one, then a hiring-manager review
  5. Take the offer, sign your Deel contract and clear the KYC identity check

How this pay compares

This job pays more than 99% of the 204 other science (PhD) jobs on the board that state pay; 0% pay more.

This job
$250/hrMiddle of $100–400/hr
Median on micro1
$65/hrFrom 287 other paid jobs
Median in science (PhD)
$65/hrFrom 204 other paid jobs
How we compare pay

Requirements

Qualifications
  • Novelty judgment
  • Research direction
  • Computational rigor
  • Complex problem solving - Research
Languages
  • English
Equipment
  • Computer with a reliable internet connection

About this job

Role Title: Principal Research Scientist (Computer Science / Computational Physics)

Role Type: Contractor (flexible, Part-Time or Full-Time)

Location: Remote

micro1 is engaging Principal Research Scientist (Computer Science / Computational Physics)s to contribute to an advanced customer project at the intersection of computational theory and AI. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. You will work with frontier AI models and agents to tackle open problems, drive research direction, and define standards for scientific breakthroughs. Your insights and rigorous approach will be pivotal in charting what counts as genuine progress within your subfield.

Scope of Work

• Identify, frame, and articulate foundational open problems, theoretical bounds, or simulation challenges where verifiable progress can be demonstrated.

• Guide AI models and agents in multi-step research processes—ranging from proofs and algorithms to numerical experiments and high-performance simulations.

• Critically assess and validate results, utilizing proof checks, computational reproduction, and formal methods to pinpoint the limits of model-generated reasoning.

• Evaluate and document the novelty, correctness, and significance of research outputs relative to current literature and established results.

• Produce clear, concise research memos detailing research attempts, partial solutions, and observed model limitations or failure patterns.

• Advise on research directions, recommending promising subfields and open problems suitable for advancement via AI models and computational tools.

Preferred Qualifications

• 7 - 10+ years of active research in computer science or mathematical/computational physics, with a strong record of scholarly contributions.

• Recognition at the field level—such as major prizes, society fellowships, or plenary/invited talks at top scholarly events.

• A consistent publication record in leading venues within your domain, with recent results published in the past year.

• Demonstrated success resolving named open problems or introducing influential concepts adopted by peers.

• Deep, hands-on experience with computational research methods: simulation, numerical analysis, algorithmic implementation, and/or high-performance computing environments.

• Proven ability to rigorously examine technical work outside your immediate area of expertise.

• Experience on program committees, editorial boards, or with formal research tools (e.g., Lean, Coq, SAT/SMT solvers) is a strong plus, as is a public record of outlining open problems or showcasing research with advanced AI systems.

Listing history

First seen on our board
(9 days ago)
Posted by micro1
(13 days ago)
Last checked
Source
micro1

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