Computational Biologist, Genetics, Biochemistry, Ecology

24-MAG

Computational biologist designing genetics, biochemistry, and ecology coding tasks for 24-MAG’s remote consulting platform. Developing reproducible solutions, grading criteria, and scientific workflows.

Posted 8/25/2026part-timeRemote • New York • 🇺🇸 United StatesMid-LevelSenior💰 $60 per hourWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing computational biology problems and workflows, utilizing programming languages such as Python and R, while ensuring reproducibility and scientific rigor. Capable of translating complex biological research into computational tasks and maintaining clear documentation.

Highest-signal resume keywords

PhD In Biology Or Related FieldExpertise In Genetics, Biochemistry, EcologyStrong Proficiency In Python And RExperience With Git/GitHub And DockerStrong Written Communication Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Computational BiologyScientific WorkflowsBiological Data AnalysisStatistical ReasoningMulti-Step Problem DevelopmentDebugging Scientific CodeReproducible Scientific ComputingBiochemical Pathways AnalysisQuantitative BiologyEcological Systems Analysis

Soft Skills

CollaborationDocumentationCommunication

Tools & Technologies

PythonRGitGitHubDocker

Industry Keywords

Computational BiologyBiological SciencesGeneticsBiochemistryEcologyQuantitative BiologyScientific ResearchPeer-Reviewed Publications

Tech Stack

Tools & technologies

DockerPython

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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

Benefits

Comp & perks

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