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Computational Biologist, Genetics, Biochemistry, Ecology

šŸ”„ 0 minutes ago

šŸ—½ New York – Remote

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šŸ’µ $60 / hour

ā± Part Time

🟔 Mid-level

🟠 Senior

šŸ‘» Ghost score 0%

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Logo of 24-MAG

24-MAG

2 - 10 employees

šŸ¤ B2B

šŸ’¼ Consulting

B2B • Consulting

24-MAG is a commercial strategy and execution firm that helps B2B organizations design and implement systems, workflows, and operating rhythms for sales, client management, and cross-functional projects. They focus on transforming scattered processes into aligned, measurable, and scalable commercial functions—covering pipeline structure, account management frameworks, and operational discipline for teams seeking efficient, intentional growth.

šŸ“‹ Description

• Develop original research-level computational biology problems • Build tasks from published papers, public datasets, open-source repositories, or independently designed scientific scenarios • Create problems requiring multi-step biological, statistical, and computational reasoning • Design scientifically defensible and reproducible solutions • Develop computational tasks involving genetics and related biological datasets • Create problems involving biochemical pathways, molecular interactions, kinetics, or quantitative biology • Develop ecological and quantitative biology tasks involving ecological systems, populations, communities, or environmental datasets • Write and validate scientific workflows using Python, R, or another relevant programming language • Develop computational setups, reference calculations, and solution validators • Debug scientific code and identify implementation or numerical issues • Build reproducible workflows suitable for automated testing • Translate complex biological research into clearly specified computational tasks • Define inputs, assumptions, constraints, and expected outputs • Produce authoritative reference solutions and supporting computational analyses • Define precise, consistent, and reproducible grading criteria • Test tasks against advanced computational systems and analyse failure modes • Refine prompts, inputs, constraints, and expected outputs based on testing • Work through a Git/GitHub pull-request workflow • Run and validate code within Docker-based environments • Respond to automated quality checks and reviewer feedback • Maintain clean, reproducible code and supporting documentation • Collaborate effectively within structured scientific software workflows

šŸŽÆ Requirements

• PhD required in Biology, Biological Sciences, Biochemistry, Genetics, Ecology, or a closely related field • Demonstrated expertise in at least two of the following: Genetics, Biochemistry, Ecology • Strong working proficiency in Python, R, or another scientific programming language • Hands-on experience using code for biological research, modelling, simulation, or data analysis • Comfortable with Git/GitHub • Experience running code in Docker or other containerised environments • Strong understanding of reproducible scientific computing • Ability to translate advanced biological research into clearly defined computational problems • Peer-reviewed publications are highly valued • Prior scientific software or research engineering experience is advantageous • Strong written communication and ability to document biological assumptions, methods, and solutions precisely • Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party • H1-B and STEM OPT support is unavailable for this engagement

šŸ–ļø Benefits

• Part-time independent contractor engagement • Fully remote • 20+ hours per week • Initial duration of approximately 6 weeks • Immediate start • Projects may be extended, shortened, or concluded based on project needs and performance

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