Computer Science (STEM) at Turing

Commitments Required: At least 6 hours per day and a minimum of 40 hours per week, with a 4-hour overlap with PST.
Employment Type: Contractor assignment; no medical or paid leave.
Duration of Contract: 5 weeks; expected start date is next week.
Payment Type: $280 per approved task.

Design challenging, realistic agentic scientific workflows across the life sciences.
Create tasks requiring multiple computational steps rather than single-script or simple question-and-answer solutions.
Develop realistic input files, scientific datasets, instructions, constraints, and expected deliverables.
Build tasks requiring agents to inspect data, select appropriate methods, execute analyses, troubleshoot problems, and synthesize results.
Create reproducible expert solutions and objectively verifiable ground truths that run in the provided sandbox environment.
Design robust automated or semi-automated grading criteria.
Ensure tasks measure scientific reasoning and execution rather than memorization.
Validate scientific assumptions, calculations, code, intermediate outputs, and final answers.
Ensure tasks are self-contained and executable in controlled, network-isolated computational environments.
Maintain high quality and throughput while responding effectively to reviewer feedback.

Ph.D., postdoctoral, or equivalent research experience in the life sciences, with strong demonstrated computational and scientific programming experience.
Strong scientific programming experience, particularly in Python.
Experience performing multi-step computational scientific analyses.
Ability to independently validate both scientific reasoning and computational outputs.

Expertise in one or more areas, including bioinformatics, computational genomics, systems biology, computational neuroscience, biostatistics, computational drug discovery, computational biochemistry, structural biology, protein engineering, or computational microbiology.
Experience with scientific libraries and command-line tools.
Experience creating reproducible research pipelines.
Ability to translate authentic research workflows into bounded, objectively gradable tasks.

Commitments Required: At least 6 hours per day and a minimum of 40 hours per week, with a 4-hour overlap with PST.
Employment Type: Contractor assignment; no medical or paid leave.
Duration of Contract: 5 weeks; expected start date is next week.
Payment Type: $280 per approved task.

Design challenging, realistic agentic scientific workflows across the life sciences.
Create tasks requiring multiple computational steps rather than single-script or simple question-and-answer solutions.
Develop realistic input files, scientific datasets, instructions, constraints, and expected deliverables.
Build tasks requiring agents to inspect data, select appropriate methods, execute analyses, troubleshoot problems, and synthesize results.
Create reproducible expert solutions and objectively verifiable ground truths that run in the provided sandbox environment.
Design robust automated or semi-automated grading criteria.
Ensure tasks measure scientific reasoning and execution rather than memorization.
Validate scientific assumptions, calculations, code, intermediate outputs, and final answers.
Ensure tasks are self-contained and executable in controlled, network-isolated computational environments.
Maintain high quality and throughput while responding effectively to reviewer feedback.

Ph.D., postdoctoral, or equivalent research experience in the life sciences, with strong demonstrated computational and scientific programming experience.
Strong scientific programming experience, particularly in Python.
Experience performing multi-step computational scientific analyses.
Ability to independently validate both scientific reasoning and computational outputs.

Expertise in one or more areas, including bioinformatics, computational genomics, systems biology, computational neuroscience, biostatistics, computational drug discovery, computational biochemistry, structural biology, protein engineering, or computational microbiology.
Experience with scientific libraries and command-line tools.
Experience creating reproducible research pipelines.
Ability to translate authentic research workflows into bounded, objectively gradable tasks.

Computer Science (STEM)