BioTalent Ltd
A clinical-stage biopharmaceutical organization focused on advancing novel cancer therapies through the development of multi-specific antibodies and antibody-drug conjugates (ADCs). With a strong pipeline that includes multiple assets in clinical development and a growing preclinical portfolio, the team is looking to expand its AI-driven drug design capabilities with a skilled Protein Design Scientist.
Job Summary:
We are seeking a creative and driven scientist to join the AI-driven drug design team, contributing to the development and optimization of a computational protein design pipeline. This individual will leverage data-driven methodologies to support the creation of innovative multi-specific biologics. A strong background in the computational design of peptides and proteins —with expertise in structural modeling, prediction , and optimization—is essential for success in this role.
Essential Duties and Responsibilities: Utilize a computational pipeline to predict properties of peptides, natural ligands, de novo proteins, and antibody-based components. Support assay validation, technology transfer, and development initiatives; contribute to yeast display-based protein discovery platforms. Leverage structural and sequence analysis to design new macromolecular therapeutics, using in silico predictions to inform lead optimization. Analyze, interpret, and clearly present data to scientific and leadership stakeholders. Collaborate cross-functionally with discovery, engineering, and immuno-oncology teams to support therapeutic innovation. Qualifications: PhD (or equivalent) in bioengineering, biophysics, biochemistry, molecular biology, cell biology, or a related discipline. 8+ years of experience utilizing yeast libraries to discover protein binders or therapeutic antibodies. Proficiency with relevant macromolecular modeling tools (e.g., AlphaFold , RoseTTAFold, RFdiffusion, ProteinMPNN, Gromacs, MOE, Schrödinger). Hands-on expertise in antibody screening methods (e.g., ELISA, multi-parametric flow cytometry, BLI/OCTET). Track record of contributing to therapeutic antibody development; experience designing and validating novel biologically relevant antibodies is highly desirable.
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Essential Duties and Responsibilities: Utilize a computational pipeline to predict properties of peptides, natural ligands, de novo proteins, and antibody-based components. Support assay validation, technology transfer, and development initiatives; contribute to yeast display-based protein discovery platforms. Leverage structural and sequence analysis to design new macromolecular therapeutics, using in silico predictions to inform lead optimization. Analyze, interpret, and clearly present data to scientific and leadership stakeholders. Collaborate cross-functionally with discovery, engineering, and immuno-oncology teams to support therapeutic innovation. Qualifications: PhD (or equivalent) in bioengineering, biophysics, biochemistry, molecular biology, cell biology, or a related discipline. 8+ years of experience utilizing yeast libraries to discover protein binders or therapeutic antibodies. Proficiency with relevant macromolecular modeling tools (e.g., AlphaFold , RoseTTAFold, RFdiffusion, ProteinMPNN, Gromacs, MOE, Schrödinger). Hands-on expertise in antibody screening methods (e.g., ELISA, multi-parametric flow cytometry, BLI/OCTET). Track record of contributing to therapeutic antibody development; experience designing and validating novel biologically relevant antibodies is highly desirable.
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