Experience: 0–4 years · Type: Full-time, On-site (Bengaluru)

The Mission

Mandrake Bio is a protein-design company building the next generation of programmable gene-editing enzymes. Its platform designs editors from scratch, pairing generative AI with first-principles biophysics and wet-lab validation to engineer the compactness, precision, and dynamic control that the highest-impact applications in agriculture and medicine demand. Founded in 2025 and headquartered in Bengaluru, India. Learn more at mandrake.bio.

We are a VC-backed, small, high-velocity applied research lab. We don't care about credentials; we care about proof of work, first-principles thinking, and the ability to ship.

What You'll Work On

• Build large-scale in-silico screening pipelines for protein/enzyme discovery, optimization, and functional characterization.
• Develop data-mining frameworks to extract, clean, and cluster large genomic, proteomic, and metagenomic datasets.
• Implement computational workflows for structure prediction, stability analysis, docking, and function annotation.
• Run high-throughput virtual screening and mutational characterization to nominate candidates for wet-lab validation.
• Integrate structural-biology tools with AI models for activity prediction and structure–function correlation.
• Partner tightly with AI and experimental teams to translate compute into validated tools — across therapeutic and agricultural programs.

You're a Great Fit If You

• Have strong footing in computational biology, protein engineering, or structural bioinformatics.
• Are fluent in Python / Biopython / PyRosetta / MDAnalysis / pandas / NumPy or equivalent.
• Have used protein modeling tools (AlphaFold, Rosetta, FoldX, docking suites, MD simulations).
• Understand sequence–structure–function relationships and biophysical determinants of stability/activity.
• Can build reproducible pipelines (Snakemake / Nextflow / Slurm / cloud) over large biological datasets.
• Think rigorously from first principles and thrive on high ownership.

Nice to Have

• Exposure to in-silico drug screening, virtual docking, or computational chemistry.