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 modelsNice to have
Experience with at least one : genomic FMs (e.g., Enformer-style, Nucleotide / Genome LMs), protein LMs (e.g., ESM / ProtT5 / MSA), or similarEnzyme / 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.