The candidate will be joining our AI fScience team to build state-of-the-art therapeutic discovery development platform, closely integrating frontier AI Automation technologies driving innovation fnext-gen biotherapeutics.
Responsibilities
•Develop, test optimize AI & ML-based models workflows to solve complex problems in biologics discovery development.
•Apply generative AI & ML-based protein design engineering technologies to design novel therapeutic antibodies, including de novo design optimization.
•Work with various teams to enhance data infrastructure lab automation integration.
•Support external partnerships collaboration opportunities.
•Analyze, interpret, document, present project results to the scientific leadership team.
•Effectively partner across multidisciplinary interfaces to achieveganizational objectives.
Qualifications
•PhD in Computer Science, Computational Biology, Biochemistry, Physics related field minimum of 3 years of experience in AI fScience projects MS minimum of 7 years industry experience.
•Familiar with mainstream AI/ML frameworks such as Pytorch Tensorflow, solid programming skills with hands-on experiences in training models such as GNNs, transformers, GANs, diffusion flow matching models etc.
•Highly curious, eager to take on challenges capable of quickly grasping project requirement implementing innovative solution.
•Outstanding written verbal communication skills, ability to work with colleagues from diverse scientific backgrounds cultures.
Preferred Skills
•Experience publishing on top-tier journals AI/ML conferences such as NeurIPS, ICML ICLR, achieving awards high rankings in international competitions such as ACM ICPC.
•Hands-on experience in model training application fprotein language models protein design optimization.
•Deep understanding of protein structure molecular biophysics.
•Experience analyzing antibody repertoires fsequence- structure-based design.
•Mastery of macromolecular modeling design tools (e.g. AlphaFold, Rosetta, RFDiffusion, ProteinMPNN, Gromacs, MOE, Schrödinger, etc)
•Experience constructing, annotating, analyzing, maintaining large databases of protein/antibody structures sequences.
•Experience deploying scalable computational workflows on HPC cloud.
•Experience creating a prototype user interface (such as a web application) fAI/data science-based solutions.
•Experience developing lab automation solutions.
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