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