1、Develop and apply AI/ML models for de novo antibody design, affinity maturation, humanization, and developability assessment. 2、Utilize specialized generation tools and platforms for antibody sequence and structure design. 3、Apply biophysical knowledge and computational software to predict and optimize antibody properties such as stability, aggregation, and immunogenicity. 4、Lead computational efforts in de novo design of antibody binding sites and fulllength antibodies. 5、Develop and implement druggability models to assess and improve the therapeutic potential of antibody candidates. 6、Analyze large-scale antibody sequencing and structural data to inform model development. 1、Education: Ph.D. in Computational Biology, Biophysics, Bioinformatics, or a related field, OR 3-5 years of relevant industry experience. 2、Antibody Expertise: Demonstrated experience with computational generation tools and platforms specifically for antibodies (e.g., sequence-to-structure, CDR design). 3、Biophysical Knowledge: Strong understanding of antibody biophysics and hands-on experience using relevant computational software for property prediction (e.g., stability, aggregation, viscosity). 4、Design Experience: Proven experience in de novo design of proteins/antibodies and the development or application of druggability models. 5、Programming: Proficiency in Python and experience with relevant scientific computing libraries.