Scientific Leader, Molecular Design

Role Summary

Scientific Leader, Molecular Design role based in the US at the Upper Providence site (Collegeville, PA) with 2-3 days on-site per week. Will join the Molecular Design team in Molecular Modalities Discovery to accelerate discovery and development of transformational medicines through computational methods, predictive in silico models, and expert analyses. Collaborates with preclinical research and development partners to influence target identification, modality selection, molecule design, and identification of clinical candidate therapeutics that will impact patients.

Responsibilities

• Collaborate with experimental groups to drive compound design and improve models using structure-based drug design, QSAR modeling, QM methods, and computational modeling of macromolecular systems.
• Predict and evaluate targets for their probability of success to be drugged across modalities including small molecules, oligonucleotides, protein degraders, and antibody-drug conjugates.
• Work with biology team members to assimilate data from experiments, optimize experiments, and integrate data into compound design.
• De novo design and multi-objective optimization of tool compounds and target-specific medicines.
• Partner with other GSK computing groups to develop and embed computational methods in visualization packages to enable multi-variate analysis and data-driven decision-making.
• Collaborate with external groups to further develop computational methods to enhance internal compound design.
• Stay up-to-date with latest developments in computational methods related to small molecules, PROTACs, DNA/RNA therapeutics, and other modalities.

Qualifications

• PhD or equivalent in Computational Chemistry, Computational Biology, Biophysics or Chemistry
• 5+ years industry experience post-graduation or postdoc
• Scientific contributions documented with publications, presentations, and/or patents
• Experience in molecular modeling, protein structure analysis, and small molecule optimization
• Experience working in a Linux/Unix environment
• Expertise in one or more scripting or programming languages (e.g., Python, Java, C++/Visual C++)

Preferred Qualifications

• Strong organizational and communication skills, with the ability to liaise and communicate complex computational procedures and outcomes with scientists and external collaborators
• Knowledge of other drug discovery disciplines and processes (medicinal chemistry, toxicology, DMPK, and/or screening data analysis)
• Present data in project team meetings and participate in writing abstracts and publications
• Independently review and appraise scientific literature
• Knowledge of cheminformatics and QSAR methods
• Lead multi-disciplinary matrix teams to address key goals, exhibiting interpersonal skills
• Experience generating/applying machine learning in QSAR and other chemo-centric predictive models
• Demonstrated research proficiency in modeling oligonucleotide/RNA therapeutics in a drug discovery environment