Assistant Professor
3 weeks ago
About Us
Atria University desires and enables research impact beyond publications. We operate without traditional departments (HoDs). Faculty are housed within Centers of Excellence (CoE), fostering deep, cross-disciplinary collaboration. This role will primarily be affiliated with the Bio-AI Hub/CoE.
Why this role
Help build India’s next wave of Bio-AI: genomic and protein foundation models, multi-omics modelling, generative design for enzymes and pathways, and AI-assisted DBTL loops with wet-lab partners. You’ll have real datasets, compute, and translational collaborations.
What you’ll do
- Lead research on Bio-AI foundation models (e.g., DNA FMs, protein LMs, generative design/diffusion for sequences/structures).
- Ship artifacts: open-source code, trained weights, datasets, and benchmarking pipelines; submit to top venues; file IP where appropriate.
- Collaborate intensively with faculty in the wet-lab/clinical CoEs to design unified, problem-driven interdisciplinary curricula and research projects (strain/enzyme design, microbiome, diagnostics, materials for bioenergy, etc.).
- Teach light, high-impact: 2–3 project-based, 4-credit sprints/year; mentor student teams on real problems.
- Win grants & lead consortia: craft proposals, coordinate multi-partner projects, and grow the Bio-AI Hub, explicitly ensuring student research teams are integrated into grant deliverables.
What will set you up for success (must-have)
- PhD (or ABD close to defense) in CS/AI/Computational Biology/Bioinformatics/Applied Math or related.
- Strong first-author record or open-source impact in sequence modelling (Transformers/GraphNNs/Diffusion) applied to genomics/proteomics.
- Hands-on with PyTorch, training/evaluating large models, and reproducible ML (MLOps, containers, Slurm/cloud).
- Exposure to workings of foundation models
Nice to have
- Experience with at least one: genomic FMs (e.g., Enformer-style, Nucleotide/Genome LMs), protein LMs (e.g., ESM/ProtT5/MSA), or similar
- Enzyme/pathway design, multi-omics integration, metagenomics.
- Joint work with wet-lab/clinical teams; familiarity with DBTL or LIMS/ELN.
- Prior grant success (PI/Co-PI) or industry collaboration.
What we offer
- Research-first load: concentrated teaching in short sprints; significant time for research.
- Compute & infra: access to GPUs, curated omics datasets, secure data rooms, and DevOps support.
- Translational runway: partnerships with industry and research organizations; pathways for IP and spinouts.
- Community: interdisciplinary peers in AI and Life Sciences; vibrant Bengaluru ecosystem.
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