Computational Antibody Design, Computational Discovery Co-Op

Job Summary
Computational Discovery is seeking an independent and self-motivated Co-Op student to contribute to the advancement of AI/ML-guided drug discovery programs. The successful candidate will contribute to development and deployment of predictive and/or generative models for antibody lead optimization. They will help curate and integrate public antibody datasets with in-house experimental data to and assist in developing computational workflows that explore large-scale sequence—structure relationships to accelerate antibody hit-to-lead optimization. This position provides exceptional learning experience in AI/ML-guided biologics design, offering experience in practical ML applications for drug discovery, literacy in structure prediction methods and experience in a fast-paced, cross-functional Biopharma team.

Key responsibilities

• Develop & deploy machine learning, deep learning, and/or physics-based models for antibody hit-to-lead optimization.
• Apply large-scale data mining and structural modeling to discover and refine antibody sequence-structure-function relationships.
• Build and automate AI workflows that integrate antibody design, feature extraction, and property prediction.
• Translate designs into testable constructs and integrate multi-dimensional assay readouts to close the design → make → test → retrain loop 
• Work cross-functionally with wet-lab teams to enable lab-in-the-loop driven drug discovery
• Contribute to data visualization, scientific documentation, and presentation of computational results to an inter-disciplinary team.

Minimum Qualifications

• Ph.D. candidate in Bioinformatics, Computational Biology, Data Science, Biostatistics or similar.
• Proficiency in Linux, Python and/or Rstudio relevant ML tools such as git, Jupyter Notebooks Scikit-Learn etc.
• Experience in leveraging statistical and machine learning approach on large datasets
• Excellent verbal and written communication skills.

Preferred Qualifications

• Experience utilizing High Performance computing (HPC) and AWS cloud computing infrastructure.
• Proficiency in Deep Learning frameworks (eg:  PyTorch, Tensorflow/Keras)
• Working knowledge of public antibody and protein data resources, such as SAbDab, Thera-SAbDab, OAS (Observed Antibody Space), IMGT, PDB, AlphaFold DB, and UniProt, and ability to extract, preprocess, and curate data for model training
• Experience in state-of-the-art applications of ML on antibody design (eg: protein language models, folding model, Structure based models)

Disclaimer: The above statements are intended to describe the general nature and level of work performed by employees assigned to this job. They are not intended to be an exhaustive list of all duties, responsibilities, and qualifications.  Management reserves the right to change or modify such duties as required.

Incyte Corporation is committed to creating a diverse environment and is proud to be an equal opportunity employer.

We Respect Your Privacy

Learn more at: http://www.incyte.com/privacy-policy

The Incyte hiring organization processes your personal data to manage your job application in order to enter into an employment relationship with you if you are the successful candidate.

 During the process, you may be asked to respond to questions that will screen out your application if you do not meet certain objective criteria required by the job.   You can learn more about this process here.

You may have the right to access, delete, restrict, edit, move, or object to the use of your personal data. You may also have a right to report concerns to the authority responsible for data privacy in the country where the position is based or where you live or work. 

You can learn more about Incyte’s data protection practices here. By accessing this link you can learn about the types of personal data we collect, how we use it, whether collection and processing is optional, sources of the personal data we process, how it is shared, where it is stored or transferred to, how long we keep it, and contact information for Incyte, Incyte’s data protection officer, and your supervisory authority (if applicable).

Please contact privacy@incyte.com if you have any questions or concerns or would like to exercise your rights.