Researcher Chemistry (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 – Chemistry (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, published papers, 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 Chemistry 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 chemistry, computation, and artificial intelligence.

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

Key Responsibilities

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

• Develop coding-based chemistry problems involving organic chemistry, inorganic chemistry, physical chemistry, analytical chemistry, computational chemistry, and chemical kinetics

• Create simulations, computational models, and data-driven experiments to evaluate AI performance

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

• Conduct quantitative research on scientific reasoning, chemical 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 chemistry, AI evaluation, AI safety, scientific computing, and machine learning

Qualification

Required

• Master's or PhD in Chemistry, Computational Chemistry, Chemical Engineering, Materials Science, Biochemistry, Computer Science, or a closely related quantitative discipline

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

• Strong foundation in organic chemistry, inorganic chemistry, physical chemistry, analytical chemistry, and chemical problem-solving

• Proficiency in Python and experience developing simulations, computational models, data analysis workflows, or scientific software

• Experience with statistical analysis, 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 Chemistry 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 chemistry, cheminformatics, molecular modeling, reaction modeling, quantum chemistry, or materials modeling

• 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, RDKit, Open Babel, Gaussian, ORCA, GROMACS, MATLAB, or similar scientific computing frameworks

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