Researcher Physics (Coding)

Company Description

Dusker AI specializes in evaluating and benchmarking advanced AI systems through rigorous, research-driven methodologies. We partner with organizations developing large language models, AI agents, and autonomous systems to measure performance across reasoning, reliability, adaptability, safety, and domain expertise.

Our evaluation frameworks are designed by subject matter experts and researchers, enabling deeper assessment than traditional benchmarks. By identifying strengths, uncovering failure modes, and testing real-world capabilities, Dusker AI helps organizations build AI systems that are robust, trustworthy, and deployment-ready.

We work across a wide range of domains including mathematics, physics, chemistry, biology, software engineering, and applied sciences, creating high-quality evaluation datasets and benchmark suites that drive the next generation of AI performance.

Role Description

Researcher – Physics (Coding)

Compensation: $20–$25 per accepted task

Location: Remote

Education Requirement: Master's or PhD

Publication Requirement: Peer-reviewed publications, conference papers, journal articles, preprints, or equivalent research contributions preferred.

Application Requirements

Applicants are strongly encouraged to include links to their Google Scholar profile, ResearchGate profile, ORCID profile, arXiv publications, personal academic website, or other verifiable research publications within their CV/Resume.

Applications with demonstrated research experience and accessible publication records will be prioritized during the review process.

We are seeking a highly analytical Physics Researcher with strong programming expertise to contribute to the design and evaluation of advanced AI systems. This remote position focuses on developing scientifically rigorous benchmarks, evaluating model reasoning capabilities, and conducting research at the intersection of physics, computation, and artificial intelligence.

The successful candidate will formulate challenging physics-based tasks, implement simulations and computational models, analyze model behavior, and develop evaluation methodologies that measure the accuracy, consistency, robustness, and reasoning abilities of advanced AI systems.

Key Responsibilities

• Design rigorous physics benchmark tasks and evaluation frameworks for AI systems

• Develop coding-based physics problems involving mechanics, electromagnetism, thermodynamics, quantum physics, optics, statistical mechanics, and computational physics

• Create simulations, numerical models, and computational experiments to evaluate AI performance

• Analyze AI-generated solutions and identify strengths, weaknesses, reasoning errors, and failure patterns

• Conduct quantitative research on scientific reasoning, problem-solving, and model reliability

• Collaborate with multidisciplinary teams to improve benchmark quality, coverage, and evaluation methodologies

• Document methodologies, findings, and evaluation results through technical reports and research summaries

• Contribute to benchmark datasets, evaluation frameworks, and internal research initiatives

• Stay informed about developments in physics, AI evaluation, AI safety, scientific computing, and machine learning

Qualification

Required

• Master's or PhD in Physics, Applied Physics, Computational Physics, Engineering Physics, Computer Science, Mathematics, or a closely related quantitative discipline

• Demonstrated research experience with peer-reviewed publications, conference papers, journal articles, or equivalent scholarly contributions

• Strong foundation in classical mechanics, electromagnetism, thermodynamics, quantum mechanics, and mathematical modeling

• Proficiency in Python and experience developing simulations, numerical methods, computational models, or scientific software

• Experience with data analysis, statistical reasoning, experimental design, and scientific computing

• Excellent written and verbal communication skills in English

• Ability to work independently in a remote research environment

Preferred

• PhD degree in Physics or a closely related field

• Multiple peer-reviewed publications in recognized journals or conferences

• Experience evaluating AI systems, machine learning models, or large language models

• Background in computational physics, numerical analysis, simulation methods, scientific computing, or high-performance computing

• Experience developing benchmarks, datasets, or evaluation frameworks

• Familiarity with AI safety, model alignment, AI benchmarking methodologies, or scientific reasoning evaluation

• Experience with tools such as Python, NumPy, SciPy, MATLAB, Mathematica, or similar scientific computing frameworks

Candidates with strong academic research backgrounds, publication records, computational physics experience, and demonstrated expertise in scientific problem-solving are especially encouraged to apply.