Hello,

Greetings from ZettaMine!!!

Freelancing Opportunity: We are hiring a POD Lead – Scientific Computing Expert (Life Sciences PhD) for a short-term Frontier AI Research, Computational Biology & Scientific Evaluation.

Location: India

Role: POD Lead – Scientific Computing Expert (Life Sciences PhD)

Educational Eligibility: PhD, postdoctoral experience, or equivalent research experience in Life Sciences, Medicine, or a closely related discipline, with strong computational and scientific programming expertise.

Mode: Remote

Start: Immediate

Mandatory Eligibility Criteria

Technical Qualification:

- PhD, postdoctoral, or equivalent research experience in Life Sciences, Medicine, or a closely related field, with demonstrated computational and scientific programming expertise.
- Strong scientific programming skills, particularly in Python.
- Previous experience working as a POD Lead in similar projects, leading and mentoring technical trainers.
- Expertise in at least one area, such as Bioinformatics, Computational Genomics, Systems Biology, Computational Neuroscience, Biostatistics, Computational Drug Discovery, Structural Biology, Protein Engineering, or Computational Microbiology.
- Ability to independently validate scientific reasoning, research methodologies, computational workflows, and analytical outputs.
- Experience reviewing scientific datasets, analysis pipelines, reference solutions, computational environments, and automated tests.
- Robust understanding of scientific accuracy, statistical methods, reproducibility, data validation, and computational evaluation.
- Ability to identify incorrect assumptions, analytical errors, unreliable results, and weaknesses in automated grading systems.
- Strong analytical and problem-solving skills, with the ability to provide clear, actionable technical feedback.
- Experience mentoring trainers, reviewing deliverables, maintaining quality standards, and ensuring timely project delivery.

Preferred Qualifications:

- Familiarity with bioinformatics tools such as Samtools,



BCFtools, GATK, BWA, STAR, Salmon, DESeq2, edgeR, Seurat, Scanpy, or Biopython.
- Familiarity with scientific workflow tools such as Nextflow, Snakemake, Docker, Conda, Git, and high-performance computing (HPC) environments.
- Knowledge of computational drug discovery and structural biology tools such as RDKit, OpenMM, GROMACS, AutoDock Vina, or PyMOL.
- Familiarity with medical imaging, clinical research, biostatistics, or biomedical data analysis tools.
- Experience designing scientific benchmarks, research challenges, or computational evaluation tasks.
- Prior experience in AI training, AI evaluation, or scientific research projects is an added advantage.

Availability

- Minimum 40 hours per week.
- Availability to work at least 8 hours per day.
- Minimum 4 hours of overlap with PST business hours.
- Immediate availability for a 3-week contract assignment.

What You’ll Work On

- Lead and mentor a pod of approximately 5–10 technical trainers developing realistic, terminal-based scientific tasks for a frontier AI training and evaluation initiative.
- Design challenging, multi-step scientific workflows across computational biology, bioinformatics, medicine, and life sciences.
- Review scientific tasks end to end, including problem statements, biological and clinical datasets, reference files, computational pipelines, environments, reference solutions, and automated tests.
- Ensure tasks reflect authentic scientific research and clinical analysis workflows that require meaningful computational reasoning.
- Validate scientific methods, statistical assumptions, calculations, code, intermediate outputs,



and final results for accuracy and reproducibility.
- Verify that computational pipelines use appropriate tools, reference databases, genome builds, annotation versions, and software dependencies.
- Evaluate outputs such as variant calls, differential gene expression, cluster assignments, protein structure metrics, survival estimates, model performance, medical image segmentation, and pharmacokinetic parameters.
- Review automated graders to ensure they assess scientific correctness and analytical quality rather than merely checking output formatting.
- Ensure tasks are reproducible and executable in controlled computational environments, with appropriate testing and validation procedures.
- Identify flawed scientific assumptions, incorrect calculations, unreliable tests, hard-coded outputs, and other evaluation weaknesses.
- Ensure datasets are appropriately licensed, public or synthetic, and de-identified, with no protected health information or unauthorized restricted-access data.
- Screen tasks for biosafety and dual-use concerns and escalate potentially harmful biological content when necessary.
- Provide actionable written feedback, track revisions, and ensure quality issues are resolved before task approval.
- Onboard trainers, allocate tasks, monitor productivity, resolve technical blockers, and maintain consistent delivery standards.
- Maintain documentation covering task guidelines, recurring issues, quality expectations, and best practices.

Offer Details

- Employment Type: Contractor assignment (no medical or paid leave).
- Contract Duration: 3 weeks.
- Expected Start: Immediate / next available project start.
- Working Hours: Minimum 40 hours per week, with at least 4 hours of overlap with PST.

Interested Candidates: Please share your updated CV and LinkedIn profile at [email protected] and complete the registration and assessment process using the links above.

Thanks & Regards,

Karthik K

ZettaMine

📌 Pod Lead - Scientific Computing Expert — Life Science PHD (India)
🏢 ZettaMine Labs
📍 India