研究员，大分子药物设计(AI方向)/Research Investigator, Biologics AIDD(博士岗)

研究员，大分子药物设计(AI方向)/Research Investigator, Biologics AIDD(博士岗) 发布于 2026-03-17 Research Research | 全职 全职 | 上海市 上海市 General Description: We are seeking a talented Research Investigator for Biologics to join our Biologics Ab Tech team. In this role, you will be embedded within biologics teams, contributing across the full drug discovery continuum—from early target exploration through lead optimization. This position focuses on applying cutting-edge AI/Machine Learning (ML) methodologies to large molecule drug discovery, particularly antibodies, to revolutionize their design, discovery, optimization, and mechanistic understanding. You will collaborate closely with antibody discovery & engineering, structural biology, and biophysics teams to translate complex biologics questions into actionable computational analyses that inform molecular design and strategic decision-making. Key Responsibilities:•Identify, develop, and implement advanced AI/ML models and solutions for antigen-antibody interactions, antibody design, engineering, and optimization. •Serve as the primary computational biology expert for biologics programs, providing end-to-end computational support to advance project milestones.•Champion innovation by leveraging expertise in ML/AI, data science, and advanced computational modeling to propose novel technical strategies addressing key biologics challenges.Required Qualifications:•Ph.D. in Machine Learning, Computer Science, Computational Biology, Biological Sciences, Structural Biology, Bioinformatics, Biophysics, Chemistry, or a closely related quantitative discipline.•Profound expertise in developing and applying state-of-the-art deep learning models, (e.g., GNNs, Transformers, Diffusion, Flow Matching and LLMs).•Hands-on experience in de novo antibody design using diffusion or foundation models (e.g., RFdiffusion, Boltzgen) to generate novel, high-affinity antibodies.•Hands-on experience in developability and multi-parameter optimization for antibodies, integrating high-throughput and automated wet-lab platforms (lab-in-the-loop approaches)•Computational protein modeling, design, and analysis (e.g., Maestro, Rosetta, MOE) for antibody engineering, ligand docking, and macromolecular interactions is a plus.•A strong teammate and scientific leader with a passion for science and drug discovery.•Publications in peer-reviewed journals demonstrating contributions to the field.•Exceptional written or oral communication skills in both

English and Chinese. General Description: We are seeking a talented Research Investigator for Biologics to join our Biologics Ab Tech team. In this role, you will be embedded within biologics teams, contributing across the full drug discovery continuum—from early target exploration through lead optimization. This position focuses on applying cutting-edge AI/Machine Learning (ML) methodologies to large molecule drug discovery, particularly antibodies, to revolutionize their design, discovery, optimization, and mechanistic understanding. You will collaborate closely with antibody discovery & engineering, structural biology, and biophysics teams to translate complex biologics questions into actionable computational analyses that inform molecular design and strategic decision-making. Key Responsibilities: •Identify, develop, and implement advanced AI/ML models and solutions for antigen-antibody interactions, antibody design, engineering, and optimization. •Serve as the primary computational biology expert for biologics programs, providing end-to-end computational support to advance project milestones. •Champion innovation by leveraging expertise in ML/AI, data science, and advanced computational modeling to propose novel technical strategies addressing key biologics challenges. Required Qualifications: •Ph.D. in Machine Learning, Computer Science, Computational Biology, Biological Sciences, Structural Biology, Bioinformatics, Biophysics, Chemistry, or a closely related quantitative discipline. •Profound expertise in developing and applying state-of-the-art deep learning models, (e.g., GNNs, Transformers, Diffusion, Flow Matching and LLMs). •Hands-on experience in de novo antibody design using diffusion or foundation models (e.g., RFdiffusion, Boltzgen) to generate novel, high-affinity antibodies. •Hands-on experience in developability and multi-parameter optimization for antibodies, integrating high-throughput and automated wet-lab platforms (lab-in-the-loop approaches) •Computational protein modeling, design, and analysis (e.g., Maestro, Rosetta, MOE) for antibody engineering, ligand docking, and macromolecular interactions is a plus. •A strong teammate and scientific leader with a passion for science and drug discovery. •Publications in peer-reviewed journals demonstrating contributions to the field. •Exceptional written or oral communication skills in both English and Chinese. 校招项目-2026春招允许投递2次，请选择适合的职位进行投递 立即投递