Join us and contribute to the discovery of medicines that will impact lives!
Hyderabad, India
About Aganitha
Accelerate 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 cutting-edge Biopharma companies and expanding our client base globally. Read about how and what solutions we build.
Aganitha (अगणित): “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.
We are specifically looking for Ph.D. & Postdoc candidates who can contribute to the following areas:
- Disease studies to identify new targets, uncover mechanisms of action and stratify patient populations using the power of:
- Single-cell multi-omics (scRNA-seq, Proteomics, Spatial Omics, Epigenomics …)
- Whole genome sequencing (WGS) and Proteogenomics
- 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, e.g:
- Antibody engineering
- RNA design and optimization
- Viral Vector optimization for advanced cell and gene therapies
- Analysis and optimisation of bio-synthesis reactions using the power of AI/ML and computational modelling of underlying cellular processes.
Educational Qualifications
- Ph.D. candidates in Computational biology or related field