Compugen’s extraordinary multidisciplinary team is one of its greatest assets. Our employees, coming from diverse backgrounds and bringing different perspectives, work together in an environment that fosters excellence, creativity, and openness. Collaboration among experts from various disciplines is fundamental to our ability to develop unique predictive drug discovery solutions and to discover and advance novel therapeutic proteins and drug targets against cancer. This integration of expertise continues to be a key driver of our growth and enables us to fulfill our mission and business objectives.
Our computational platform sits at the heart of everything we do, driving a growing pipeline of first-in-class immuno-oncology programs and fueling collaborations with leading pharmaceutical partners. We are a science-driven, collaborative organization where computational and experimental scientists work side by side to turn discovery into therapies that matter for patients.
We are looking for a Computational Biologist to focus on Computational antibody design, playing a central role in the design and optimization of our therapeutics antibodies, while also conducting multi-omics analysis tasks within the group.
עיקרי התפקיד
You will: Work closely with our computational biologists multidisciplinary team and with the Antibody discovery functional unit
Drive computational antibody design, applying state-of-the-art computational and AI models to design and optimize multispecific therapeutics antibodies
Translate engineering concepts into experimentally validated candidates
Act as a scientific liaison with external CROs on antibody design and optimization projects as needed
Explore new methods that expand Compugen's computational antibody design capabilities, including making effective use of AI/ML-based tools
Conduct end-to-end broader computational analyses including multi-omics datasets for target analysis, as needed
Communicate scientific results and design rationale clearly to internal and external audiences
דרישות
M.Sc. or Ph.D. in Bioinformatics/Computational Biology/Structural Biology/Protein Engineering, or a closely related field
3–5 years of relevant experience in the biotech or pharmaceutical industry
Hands-on experience in computational methods for Ab developability and optimization: humanization, sequence liabilities, immunogenicity, structural and epitope predictions
Proficiency in protein model tools (e.g., PyMOL)
Familiarity with current, state-of-the-art AI based models for antibody design and sequence optimization
Proficiency in a scripting/programming language for data analysis (e.g., Python), and experience working with foundational models and LLM-based coding agents
Familiar with multi-omics datasets and analysis
Professional Attributes
Strong communication and collaboration skills, and a positive, can-do attitude
Strong analytical and troubleshooting skills
Ability to work independently while contributing effectively in a collaborative team environment
Ability to work effectively in a dynamic, cross-functional research environment
Excellent written and verbal communication skills in English
יתרון
Experience in bispecific and multispecific antibody design
Experience with yeast and phage display libraries
Experience in affinity maturation, antibody humanization, immunogenicity assessment, and developability assessment, including PTM liabilities, aggregation, and stability evaluation
Experience with AI-based applications for antibody optimization and engineering