Computational Biologist, Genetics, Biochemistry, Ecology

This is a fully remote position, open to applicants in New York.

📋 Description

• Create original research-level computational biology challenges.

• Develop tasks derived from published studies, public datasets, open-source repositories, or self-designed scientific scenarios.

• Formulate problems that necessitate multi-step biological, statistical, and computational reasoning.

• Design scientifically sound and reproducible solutions.

• Generate computational tasks related to genetics and associated biological datasets.

• Develop challenges that encompass biochemical pathways, molecular interactions, kinetics, or quantitative biology.

• Create ecological and quantitative biology tasks concerning ecological systems, populations, communities, or environmental datasets.

• Write and verify scientific workflows using Python, R, or another relevant programming language.

• Establish computational setups, reference calculations, and solution validators.

• Debug scientific code and pinpoint implementation or numerical issues.

• Construct reproducible workflows appropriate for automated testing.

• Convert complex biological research into clearly defined computational tasks.

• Specify inputs, assumptions, constraints, and anticipated outputs.

• Produce authoritative reference solutions and associated computational analyses.

• Establish precise, consistent, and reproducible grading criteria.

• Evaluate tasks against advanced computational systems and analyze failure modes.

• Refine prompts, inputs, constraints, and expected outputs based on testing outcomes.

• Utilize a Git/GitHub pull-request workflow.

• Execute and validate code within Docker-based environments.

• Respond to automated quality assessments and reviewer comments.

• Maintain clean, reproducible code along with supporting documentation.

• Collaborate effectively within structured scientific software workflows.

⛳️ Requirements

• PhD is required in Biology, Biological Sciences, Biochemistry, Genetics, Ecology, or a closely related discipline.

• Proven expertise in at least two of the following areas: Genetics, Biochemistry, Ecology.

• Strong working proficiency in Python, R, or another scientific programming language.

• Practical experience utilizing code for biological research, modeling, simulation, or data analysis.

• Comfortable using Git/GitHub.

• Experience executing code in Docker or other containerized environments.

• Solid understanding of reproducible scientific computing.

• Capability to translate advanced biological research into well-defined computational challenges.

• Peer-reviewed publications are highly regarded.

• Prior experience in scientific software or research engineering is a plus.

• Excellent written communication skills and the ability to document biological assumptions, methods, and solutions accurately.

• Work must be conducted without utilizing confidential or proprietary information belonging to any employer, client, institution, or other third party.

• H1-B and STEM OPT support is not available for this engagement.

🏝️ Benefits

• Part-time independent contractor position.

• Fully remote work opportunity.

• 20+ hours of work per week.

• Initial engagement duration of approximately 6 weeks.

• Immediate start available.

• Projects may be extended, shortened, or concluded based on project requirements and performance.