Scientific Leader, Molecular Design

We are seeking a highly motivated individual to join our Molecular Design team in Molecular Modalities Discovery. At GSK, we aim to efficiently accelerate the discovery and development of transformational medicines through the integration of advanced computational methods, predictive in silico models, and expert analyses. The successful applicant will collaborate with preclinical research and development business partners to impact various phases of the discovery process - from target identification, modality selection, and molecule design to ultimately identify clinical candidate therapeutics that will greatly improve and impact the lives of patients we serve.

This role is based in the US at our Upper Providence site in Collegeville, PA. 2-3 days on‑site per week average presence is required.

• Collaborate with experimental groups to drive compound design and improve models using structure‑based drug design, QSAR modeling, QM methods, and methods of computationally modeling macromolecular systems.
• Predict and evaluate targets for their probability of success to be drugged across various modalities including small molecules, oligonucleotides, protein degraders and antibody drug conjugates.
• Work with biology team members to assimilate data from experiments, optimize those experiments, and integrate that 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 experimental multi‑variate analysis and data‑driven decision‑making.
• Collaborate with external groups to further develop computational methods to enhance our internal compound design.
• Stay up‑to‑date with the latest developments in computational methods as they relate to small molecules, PROTACs, DNA/RNA therapeutics and other modalities.

BASIC 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++)

• Strong organizational and communication skills (both written and oral), 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, for example: medicinal chemistry, toxicology, DMPK, and/or screening data analysis
• Present data in project team meetings and participate in the writing of 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 excellent interpersonal skills
• Experience generating/applying machine learning in QSAR and other chemo‑centric predictive models
• Demonstrated research proficiency in modeling of oligonucleotide/RNA therapeutics in a drug discovery environment.

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