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Exscientia is an AI-driven pharmatech company committed to discovering, designing, and developing the best possible drugs in the fastest and most effective manner. Exscientia developed the first-ever functional precision oncology platform to successfully guide treatment selection and improve patient outcomes in a prospective interventional clinical study, as well as to progressing the first AI-designed drugs into the clinical setting.

By designing better drugs, faster, we believe the best ideas of science can rapidly become the best medicines for patients

We’re seeking a Structural Biologist, specializing in cryo-EM, with over 2 years of relevant experience in industry, to support our AI-driven Drug Discovery and Biologics platform. We are designing a truly novel, data and process centric platform and this is a fantastic opportunity to apply your hard-earned skills in a team first mission driven company.

As a Structural Biologist (cryo-EM) you will have the opportunity to:

• Solve structures of ligand-protein, protein-protein, and antibody-antigen complexes in a cryo-EM pipeline that will be integrated within Exscientia’s AI-driven design and automation platform for Biologics & Drug Discovery
• Enable high-throughput single particle cryo-EM analysis, focusing on grid preparation, data collection, image processing, & structural classification of multiple samples
• Closely interact with the Projects’ teams and Computational design teams to present the experimental structural data and actively contribute to the hypothesis-data cycles
• Perform epitope mapping studies at various atomic resolutions to validate computational design and docking protocols
• Support the implementation of automated cryo-EM data storage and processing on cloud infrastructure
• Liaise with internal and external partners, vendors, or consortia

What’s Required?

• Ph.D. degree in Structural Biology, Biophysics, Biochemistry, or related disciplines, with graduate or postdoctoral experience focusing on the structural determination of biomolecules with cryo-EM
• Expert in single particle cryo-EM workflows: grid preparation, data collection, image processing, and 2D to 3D classification
• Solid expertise in de novo model generation including standard model building, multiple conformation structure manipulation
• Proven background with relevant data processing software packages: e.g., Phenix, Relion, CryoSPARC, Scipion, Topaz, RosettaEM and CCP4EM.
• Solid knowledge and track record of structure validation and deposition using Empiar, EMDB and RCSB
• Full mastery of software for 3D structure visualization: e.g., Coot, Pymol, Chimera(X)
• Expertise in small molecule drug discovery oriented structural biology (restraint generations, geometry optimization, pose determination etc.).
• Familiar with GLP compliant lab practice and data management procedures (ELN/LIMS system)
• Peer-reviewed publications focused on cryo-EM and related structural & biophysical characterization methods

What’s Desirable?

• Experience with high-throughput cryo-EM technology, such as EPU Multigrid
• Experience with cryo-electron tomography
• Experience with model generation into cryo-EM densities using structure-prediction algorithms: AlphaFold2, RosettaFold2, ModelAngelo, DeepTracer
• Experience with Biophysical methods for sample preparation, protein purification & characterization, focusing on protein analytics, binding kinetics, and folding stability

Benefits