Role Description
This role involves building reproducible pipelines for genomics and proteomics data, applying machine learning and statistical methods to sequence, expression, or imaging datasets.
- Surface meaningful biological signals that drive scientific discovery and AI-powered biological research.
- Ideal for candidates at the intersection of biology, data science, and machine learning.
Qualifications
- Background in bioinformatics, computational biology, or related fields.
- Proficient in Python and R, with libraries like pandas, NumPy, SciPy, and scikit-learn.
- Hands-on experience with Biopython and formats like FASTA and VCF.
- Skilled in building reproducible pipelines for large-scale biological data.
- Understanding of genomics, proteomics, and molecular biology datasets.
- Experience with statistical modeling and ML methods for biological data.
- Use of Jupyter notebooks or similar tools for experimentation and collaboration.
- Care about bridging biology, computation, and AI research.
Requirements
- Design and implement reproducible pipelines for genomics, proteomics, and imaging datasets.
- Apply machine learning and statistical models to biological sequence and expression data.
- Use Biopython and scikit-learn to extract meaningful biological signals.
- Work with FASTA, VCF, and related data formats in large-scale pipelines.
- Collaborate with AI researchers and biologists to integrate bioinformatics into research.
- Document workflows to ensure reproducibility and transparency in biological analysis.
Benefits
- Classified as an hourly contractor to Mercor.
- Paid weekly via Stripe Connect, based on hours logged.
- Part-time (20–30 hrs/week) with flexible hours—work from anywhere, on your schedule.
- Weekly Bonus of $500–$1000 USD per 5 tasks.
- Remote and flexible working style.
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