Job Description:
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 innovative 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!
Work with R&D teams of our Biopharma clients, and collaborate with a team of Biologists, Medicinal Chemists, Computational Biologists, Data Scientists, Data Engineers, Web Developers, Cloud Engineers and Solution Architects to create the next generation of innovative computational chemistry solutions for target discovery and validation.
Identify areas of application for AI in Chemistry and related Lifesciences, and develop novel algorithms to drive data driven drug discoveryDrive lead discovery projects by proposing testable hypothesisApply latest advances and develop methods for data mining and performing analysis of large datasetsInvestigate statistical approaches for analysis of High Throughput Screening (HTS) dataParticipate in collecting, quality control, normalization, modeling, and other such detailed analyses of specific HTS and/or ‘omics data setsDevelopment of processes and customizable workflows that can be adapted and applied across portfolioImplement compound library design, QSAR, docking, virtual screening, molecular fragmentation, structure-based drug design, pharmacophore generation and analysis, or multi-parameter optimizationLeverage structure-based and ligand-based design techniques like protein modeling, virtual screening, QSAR, molecular dynamics simulations
Masters or Ph.D. in Chemistry with focus on computational methods
Expertise in DFT, QM/MM and CheminformaticsExperience with computational chemistry software, such as protein structure viewers, ChemAxon toolkits, RDKit, and KNIMEExperience in the use of open source and proprietary databases, such as ChEMBL, PubChem, PDB, Uniprot, AlphaFoldDB, Dotmatics, LiveDesign and OpenTargetsA working knowledge of data mining platforms (Spotfire, R shiny, Stardrop, etc.)Excellent communication skills with a desire to work in multidisciplinary teamsDemonstrated expertise in at least two areas from: virtual screening/docking, de novo design, compound redesign or optimization, molecular dynamics simulation, Markov State Models, free energy perturbation, QSAR, DMPK models |
