Domain Expert: Mathematics

Full-time

Remote

Skills

PhD Maths

Overview

About Turing:

Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality data, evaluations, and reinforcement learning environments that improve model capabilities in coding, reasoning, tool use, and multimodality. In coding, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across Financial Services, Life Sciences, Healthcare, Retail, Automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models.

Role Overview:

We are hiring US-based academic dermatologists to contribute senior clinical expertise to data curation for frontier AI models and labs. The work supports a longitudinal dermatology dataset used by AI developers, regulatory teams, and academic groups. This is the senior reviewer track of the project. You will lead clinical review on complex cases, contribute to the development of clinical evaluation frameworks, and serve as expert advisor for client teams reviewing AI model outputs.

The role is designed for dermatology faculty who want their academic expertise to count toward something rigorous, and who are interested in AI evaluation, methodology, and the durable infrastructure of clinical AI.

What You'll Do Day-to-Day:

Lead senior-level clinical review on complex or ambiguous cases.
Facilitate structured resolution of clinical disagreement among reviewers.
Contribute to the development of clinical evaluation frameworks.
Provide expert advisory hours to client teams reviewing AI model outputs
Author guideline-aligned clinical commentary on cases as needed.
Provide subspecialty consultation as appropriate

Requirements:

Faculty appointment at the rank of Assistant Professor or above at an accredited US medical school or academic medical center
Minimum 3 years post-residency completion
Board-certified in dermatology by the American Board of Dermatology
Active medical license in good standing in at least one US state
Active clinical practice
Subspecialty fellowship training (dermatopathology, Mohs/procedural, pediatric, or complex medical dermatology).
Publication record in peer-reviewed dermatology journals.
Prior exposure to clinical AI evaluation, digital health, or dermatology AI research (desired).
Active involvement with AAD, ASDS, or other dermatology specialty societies.
Prior journal peer review experience Prior IRB or research committee service.
Experience teaching residents or fellows.
Deep familiarity with current dermatology guidelines.
Strong written articulation of clinical reasoning suitable for peer review
Ability to lead and document clinical consensus
Comfort with graphic medical images and clinical complexity
Disciplined adherence to project protocols

Perfomance Expectations:

Senior reviewer responsibility on assigned case batches.
Clinically defensible documentation.
Consistent reliability with peer faculty reviewers
Constructive client-facing communication during advisory hours.
Conflict of interest disclosure.
Applicants will be asked to disclose any active equity, advisory, consulting, or paid relationships with dermatology AI companies, digital health platforms, or pharmaceutical companies whose products may appear in case content.
Disclosed conflicts do not automatically disqualify applicants but will be considered in case assignment.

Perks of Freelancing with Turing:

Conduct senior-level reviews of complex or ambiguous mathematical problems and AI-generated solutions.
Evaluate responses for mathematical correctness, logical consistency, completeness, clarity, and adherence to instructions.
Verify proofs, derivations, calculations, definitions, assumptions, notation, and final conclusions.
Identify logical gaps, unsupported claims, invalid transformations, computational errors, and counterexamples.
Assess whether alternative solution methods are mathematically valid and appropriately justified.
Facilitate the structured resolution of disagreements among mathematics reviewers.
Develop and refine evaluation rubrics, review guidelines, and quality standards.
Provide expert advisory support to client teams reviewing AI model performance.
Write rigorous, publication-quality mathematical explanations and reviewer feedback.
Provide consultation within relevant mathematical specializations.
Document review decisions and expert consensus clearly and consistently.
Follow all project protocols, confidentiality requirements, and quality standards.

Required Qualifications

PhD in Mathematics, Applied Mathematics, Statistics, or a closely related discipline from an accredited institution.
Faculty appointment at the rank of Assistant Professor or above at an accredited US university or academic institution.
At least three years of postdoctoral, faculty, or equivalent professional research experience.
Active involvement in mathematical research, teaching, or academic supervision.
Strong command of advanced mathematical reasoning, proof construction, and problem-solving.
Demonstrated publication record in peer-reviewed mathematics or interdisciplinary scientific journals.
Experience teaching undergraduate or graduate-level mathematics.
Strong written communication skills and the ability to explain complex mathematical reasoning clearly.
Ability to evaluate multiple valid approaches and determine whether solutions are complete and mathematically defensible.
Experience reviewing research papers, journal submissions, examination questions, proofs, or technical content.
Ability to lead and document expert consensus.
Strong attention to detail and disciplined adherence to evaluation protocols.

Relevant Areas of Expertise

Expertise in one or more of the following areas is preferred:

Algebra and abstract algebra
Linear algebra
Calculus and mathematical analysis
Real and complex analysis
Differential equations
Discrete mathematics
Number theory
Geometry and topology
Probability theory
Mathematical statistics
Combinatorics
Optimization and operations research
Numerical analysis
Mathematical logic
Dynamical systems
Applied and computational mathematics
Mathematical modeling
Financial mathematics
Graph theory
Information theory

Preferred Qualifications

Prior experience with AI evaluation, mathematical data annotation, or large language model research.
Experience developing mathematical rubrics, benchmarks, or assessment frameworks.
Familiarity with computational tools such as Python, R, MATLAB, Mathematica, Maple, SageMath, or similar platforms.
Experience with mathematical modeling, symbolic computation, simulations, or numerical methods.
Prior journal peer-review or editorial experience.
Service on research, academic, grant-review, or curriculum committees.
Experience mentoring graduate students, postdoctoral researchers, or junior faculty.
Active participation in the American Mathematical Society, Mathematical Association of America, or another recognized professional organization.
Familiarity with evaluating AI-generated proofs, derivations, calculations, and mathematical explanations.

Performance Expectations

Take senior-review responsibility for assigned problem batches.
Deliver mathematically accurate and defensible evaluations.
Maintain consistent quality and reliability across assignments.
Clearly document errors, assumptions, logical gaps, calculations, and final review decisions.
Collaborate constructively with other faculty-level reviewers.
Communicate professionally with client teams during advisory sessions.
Meet agreed deadlines and project quality requirements.
Maintain confidentiality and comply with all project protocols.