Remote Pod Lead - Life Sciences

About the role

Turing, an AGI infrastructure company, is hiring a remote Life Sciences or Medicine expert to lead a pod of trainers building realistic, terminal-based scientific and technical tasks for Terminal Bench Science. The pod lead reviews every task for scientific correctness, reproducibility, data compliance and grader reliability, and coaches trainers to deliver high-quality, challenging tasks. This is a 5-week contractor assignment starting next week, with no medical or paid leave.

Key responsibilities

• Review trainer tasks end to end: task statements, datasets, reference files, pipelines, environments, reference solutions and automated tests.
• Check that tasks reflect authentic research or clinical workflows and require genuine multi-step scientific reasoning.
• Verify that tools, genomes, annotations, databases and dependencies are pinned and pipelines are reproducible.
• Validate scientific correctness, including genome builds, coordinate conventions, normalization, batch effects, statistical assumptions, multiple-testing correction, units, dosing conventions, imaging orientation and random-seed control.
• Ensure graders check substantive outputs (variant calls, differential expression, clustering, binding metrics, survival estimates, model performance, segmentation accuracy, pharmacokinetics) rather than formatting.
• Ensure tolerances allow legitimate stochastic and numerical variation while rejecting incorrect analyses, and that tasks cannot be gamed.
• Confirm data is synthetic, public, licensed and de-identified, with no protected health information; screen for biosafety and dual-use concerns and escalate dangerous content.
• Provide clear written feedback, track revisions, onboard and mentor trainers, allocate work, track quality and throughput and escalate blockers.
• Maintain pod documentation covering guidelines, recurring issues and exemplary tasks.

Required profile

• Ph.D., M.D., M.D.-Ph.D., postdoctoral experience or equivalent advanced experience in a life science, biomedical or medical field with a substantial computational component.
• Proven experience reviewing code, analyses, manuscripts or research outputs.
• Experience mentoring or leading small technical or research teams.
• Excellent written communication skills for precise, constructive feedback.

Required skills

• Strong programming in Python or R, plus Bash, with Linux and terminal proficiency.
• Hands-on experience with bioinformatics pipelines, computational biology, biostatistics, medical imaging analysis or clinical data analysis.
• Strong understanding of experimental design, statistical inference and reproducibility.
• Preferred: bioinformatics tools (samtools, bcftools, GATK, BWA, STAR, Salmon, DESeq2, edgeR, Seurat, Scanpy, Biopython, Bioconductor, Nextflow, Snakemake), imaging tools (pydicom, nibabel, SimpleITK, MONAI, FSL, lifelines, statsmodels, FHIR), Docker, Conda, Git, CI systems, automated testing and HPC; experience designing benchmarks or evaluating AI coding or terminal agents.