Scientist (Bioinformatics & Computational Biology)

Join us and contribute to the discovery of medicines that will impact lives! Aganitha is accelerating drug discovery and development for Biopharma and Biotech R&D with in silico solutions leveraging Computational Biology & Chemistry, High throughput Sciences, AI, ML, HPC, Cloud, Data, and DevOps. In silico solutions are transforming the biopharma and biotech industries. Our cross-domain science and technology team of experts embark upon and industrialize this transformation. We continually expand our world-class multi-disciplinary team in Genomics, AI, and Cloud computing, accelerating drug discovery and development. What drives us is the joy of working in an innovation-rich, research-powered startup bridging multiple disciplines to bring medicines faster for human use. We are working with several innovative Biopharma companies and expanding our client base globally. Aganitha, which means countless or limitless in Sanskrit, serves as a reminder and inspiration about the limitless potential in each one of us. Come join us to bring out your best and be limitless! Key Responsibilities - Develop and apply AI & computational models in SMOL, mAb, Gene & RNA therapy design and development. - Specifically looking for Ph.D. & Postdoc candidates who can contribute to disease studies, target identification, uncover mechanisms of action, and patient population stratification using various technologies such as Single-cell multi-omics, Whole genome sequencing, Proteogenomics, and High-throughput pre-clinical experimentation datasets. - De novo design, characterization, and optimization of therapeutic candidates in silico using computational omics and chemistry models and AI. This includes Antibody engineering, RNA design and optimization, and Viral Vector optimization for advanced cell and gene therapies. - Analysis and optimization of bio-synthesis reactions using AI/ML and computational modeling of underlying cellular processes. Educational Qualifications - Ph.D. candidates in Computational biology or related field.,