Scientist - Cheminformatics, Computational Chemistry

Key Skills

AI technology, Cheminformatics, Data Modeling, Effective communication skills, Hypothesis testing, Large data sets, Python Programming, R-Shiny, Scala Programming, Spotfire, SQL, Statistical modeling

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.

Key Responsibilities

Work with R&D teams of our Biopharma clients, and collaborate with a team of Biologists, Medicinal Chemists, Computational Chemists, Data Scientists, Data Engineers, Web Developers, Cloud Engineers, and Solution Architects to create the next generation of innovative computational biology solutions for drug discovery and development.

• Identify areas of application for AI in Chemistry and related Lifesciences, and develop novel algorithms to drive data driven drug discovery
• Drive lead discovery projects by proposing testable hypothesis
• Apply latest advances and develop methods for data mining and performing analysis of large datasets
• Investigate statistical approaches for analysis of High Throughput Screening (HTS) data
• Participate in collecting, quality control, normalization, modeling, and other such detailed analyses of specific HTS and/or ‘omics data sets
• Development of processes and customizable workflows that can be adapted and applied across portfolio
• Implement compound library design, QSAR, docking, virtual screening, molecular fragmentation, structure-based drug design, pharmacophore generation and analysis, or multi-parameter optimization
• Leverage structure-based and ligand-based design techniques like protein modeling, virtual screening, QSAR, molecular dynamics simulations

Desired Skills

• Masters or Ph.D. in Chemistry with focus on computational methods
• Expertise in DFT, QM/MM and Cheminformatics
• Experience with computational chemistry software, such as protein structure viewers, ChemAxon toolkits, RDKit, and KNIME
• Experience in the use of open source and proprietary databases, such as ChEMBL, PubChem, PDB, Uniprot, AlphaFoldDB, Dotmatics, LiveDesign and OpenTargets
• A working knowledge of data mining platforms (Spotfire, R shiny, Stardrop, etc.)
• Excellent communication skills with a desire to work in multidisciplinary teams
• Demonstrated 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