Researcher Biology (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 Descriptions

Researcher – Biology (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 Biology 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 biology, computation, and artificial intelligence.

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

Key Responsibilities

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

• Develop coding-based biology problems involving genetics, molecular biology, genomics, bioinformatics, microbiology, physiology, ecology, and biotechnology

• Create computational analyses, biological simulations, 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, biological 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 biology, bioinformatics, AI evaluation, AI safety, and machine learning

Role Qualifications

Required

• Master's or PhD in Biology, Molecular Biology, Genetics, Biotechnology, Bioinformatics, Computational Biology, Biomedical Sciences, Life Sciences, or a closely related discipline

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

• Strong foundation in genetics, molecular biology, cell biology, physiology, biochemistry, and biological data analysis

• Proficiency in Python, R, or other scientific programming languages

• Experience developing computational workflows, biological analyses, statistical models, simulations, or bioinformatics pipelines

• Experience with experimental design, data analysis, and scientific research methodologies

• Excellent written and verbal communication skills in English

• Ability to work independently in a remote research environment

Preferred

• PhD degree in Biology, Bioinformatics, Computational Biology, Biotechnology, or a related field

• Multiple peer-reviewed publications in recognized journals or conferences

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

• Background in genomics, transcriptomics, proteomics, systems biology, computational biology, or bioinformatics

• 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, R, Bioconductor, BLAST, Biopython, Galaxy, Nextflow, Snakemake, or similar bioinformatics platforms

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