Investigator, Protein Design and Informatics

As an Investigator in the Protein Design & Informatics (PDI) team, you will focus on developing, integrating, and embedding advanced computational methods and predictive in silico models that accelerate discovery of medicines. Included in the larger Data & Predictive Sciences department, you'll be working daily with a diverse group of data/ML scientists, cheminformaticians, bioinformaticians, and many others, to impact from target discovery to the clinic - all stages of a therapeutic project.,

• Work with partner functions to generate, validate, and integrate sequence-/structure-based generative AIML models for the de novo design and multi-objective optimization of tool and therapeutic biologics, such as antibodies, antigens, peptides, ADCs, and oligonucleotides.
• Innovate, develop, and apply predictive models for protein design and developability engineering, utilizing large-scale NGS, patient-derived, and other proprietary in-house and external data sources.
• Build agent-orchestrated, integrated Design-Make-Test cycles with automated platforms generating quality data at scale.
• Identify and advocate for the opportunities afforded by scientific computation and platform automation and champion a "predict-first" culture by maximizing use of predictive technology in experimental lines.
• Collaborate with external groups to further develop protein engineering computational methods., We believe in an agile working culture for all our roles. If flexibility is important to you, we encourage you to explore with our hiring team what the opportunities are.
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• PhD or equivalent in Bioinformatics, Physics, Chemistry, Computer Science, Structural Biology, or related fields
• Experience in protein structural or sequence analysis
• Experience in one or more programming languages (e.g. Python, C/C++)
• Demonstrated ability to work as team lead or member; ability to work/lead effectively in a matrix environment
• Demonstrated evidence of working across scientific and technical disciplines to deliver impactful solutions that drive project progression
Preferred Qualifications & Skills: Please note the following skills are not necessary, just preferred, if you do not have them, please still apply:
• Experience developing or applying modern ML architectures for sequence- or structure-based protein design models (LLMs, diffusion models, flow-matching, GNNs, etc.)
• Experience predicting and analyzing protein-protein interactions and surfaces for design
• Experience with engineering production-ready robust and scalable scientific workflows
• Experience analyzing antibody repertoires for sequence- and structure-based design
• Experience predicting structures of RNA or nucleic acid-protein complexes
• Experience with molecular simulation techniques
• Demonstrated learning agility, and scientific curiosity while maintaining focus on driving greater impact in the face of uncertainty and change
• Ability to generate conclusion reports, present data in team meetings and participate in writing of abstracts and publications for the scientific community
  
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