Assistant Professor

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.