katamaran industries Pvt. Ltd.

Job Title:** Computational Immunologist AIDriven Antibody Design *Location:* Bengaluru (Whitefield) HQ *Job Type:* Fulltime | On site/Hybrid *Industry:* Biotechnology | AIDriven Drug Discovery *Function:* R\&D | Computational Biology | Machine Learning | Immunology --- Impact Leverage generative protein models and your expertise in tumorimmune interactions to *slash antibody hittolead timelines 6 and cut wetlab cost 70%*, bringing firstinclass therapies to patients faster. --- About the Role We’re a venturebacked biotech startup pioneering AIfirst approaches to therapeutic discovery. You’ll join a crossfunctional team of computational scientists, immunologists and automation engineers to design the next wave of antibodies, bispecifics and Tcell engagers. Your code—and your immunology insight—will directly steer discovery campaigns from datadesigndrug. --- Key Responsibilities * *AIDriven Design & Optimization* – Deploy sequencetostructure pipelines (AlphaFold2/Rosetta/OmegaFold) and generative models (ESM2, VAEs, diffusion) to engineer antibodies and TCEs for optimal affinity, specificity, and immune effector function (ADCC, CDC, checkpoint blockade). * *ImmunoOncology Modeling* – Mine immunerepertoire, bulk/SCRNAseq and spatialomics datasets to discover novel epitopes, resistance mechanisms and antigendensity thresholds across tumor types. * *Model Development & Benchmarking* – Design, train and evaluate ML/DL models on largescale biological data; compare predictors for immunogenicity, developability and Fceffector performance. * *Computational Workflow Engineering* – Build reproducible, containerized (Docker/Snakemake) pipelines on cloud GPUs (AWS/GCP) for highthroughput designbuildtest loops. * *CrossFunctional Collaboration* – Work handinhand with wetlab teams to validate designs in patientderived tumoroids and syngeneic models; iterate rapidly based on realworld data. * *Data Interpretation & Visualization* – Analyze highthroughput assay outputs; present insights clearly to multidisciplinary stakeholders. * *Open Science & Documentation* – Contribute to opensource tooling, maintain robust GitHub repos and champion reproducible research practices. --- First90Day Goals 1. *Ship* an automated sequencetostructure pipeline (PyTorch+AlphaFold2) that scores affinity and effectorfunction metrics. 2. *Establish* an immunecontextual benchmarking set spanning 5 tumor types to evaluate ADCC potential and antigen density. 3. *Validate* 10 designed variants in patientderived tumoroids; feed results back to improve models. --- Qualifications * *Education* – PhD/MSc in Immunology, Cancer Biology, Computational Biology, Bioinformatics, or related field. * "Core Expertise and Technical Skills" * Deep understanding of tumor immunology, antibody structure–function and immuneevasion pathways. * Proficient in Python; experience with PyTorch/JAX/Tensorflow * Familiarity with protein LM & generative models (ESM, ProtBert, VAEs, diffusion). * Practical with structural tools (AlphaFold2, Rosetta) and graph neural networks. * Experience scaling ML pipelines on cloud compute (AWS/GCP) and containerized workflows. – Expertise in Fcengineering, bispecific/TCE design, multiobjective optimization, or PK/PD modeling. * Familiarity with Statistical modeling and data visualization * Familiarity with core generative models architectures (GANS/VAE's/Transformers) --- Why Join Us? * Work at the frontier of *AIImmunoOncology* in a missiondriven, fastpaced environment. * Collaborate with worldclass scientists, engineers and therapeutic leaders. * Clear growth path into TechLead or Principal Scientist roles as we scale. --- Note: We welcome applicants from nontraditional backgrounds who can demonstrate excellence via opensource contributions, Kaggle competitions or relevant project portfolios.