Postdoc Deep protein representation learning for drug discovery

Short introduction

Are you passionate about deep learning and excited about its potential to transform drug discovery? We are looking for a talented postdoctoral researcher to join our ERC-funded project at TU Eindhoven, where we develop cutting-edge deep learning methods for protein representation and small-molecule drug discovery.

Proteins play a crucial role as mediators of the therapeutic potential of molecules. Capturing meaningful information on proteins with AI has an enormous potential in drug discovery and chemical biology, e.g., for structure-based drug discovery and polypharmacology. Despite such potential, strategies to capture sophisticated information on protein structure with deep learning are underexplored compared to small molecules.

This ERC-funded project has the ambitious goal to develop new AI strategies to learn efficiently from protein structures, to ultimately accelerate small molecule drug discovery. The project will be fueled by methodological innovation and aimed to leverage large corpora of protein data with cutting-edge deep learning algorithms. The developed approaches will be applied experimentally for structure-based drug discovery, thereby providing a unique opportunity to validate the AI predictions in a real-world setting.

Job Description

Your tasks will include:

• Developing and implementing innovative representation learning algorithms (e.g., using geometric deep learning and/or multimodal approaches) to capture sophisticated structural information for structure-based drug discovery.
• Implementing cutting-edge deep learning approaches to efficiently learn from large corpora of protein structures.
• Collaborating and interacting with ongoing research in deep learning for drug discovery, as well as in medicinal chemistry and chemical biology.
• Mentoring and supervising junior researchers and students who are working on deep-learning-assisted drug discovery.
• Communicating the results of your research through publications in scientific journals and presentations at conferences.

You will work at the interface between deep learning, chemistry, and biology, with a proactive and interdisciplinary attitude. You will become a member of the Molecular Machine Learning group (led by Prof. Francesca Grisoni), whose mission is to augment human intelligence in drug discovery with novel computational technology. You will also be embedded in the Chemical Biology cluster, the Department of Biomedical Engineering, the Institute for Complex Molecular Systems, and the Eindhoven AI Systems Institute – characterized by a highly interdisciplinary and collaborative approach to science and research.

Job Requirements

Background:

• A PhD degree in Computer Science, Computer Engineering, Bioinformatics, or related disciplines.
• Expertise in deep learning, and in handling unstructured data such as graphs and sequences.
• Basic understanding of molecular biology and/or medicinal chemistry is desirable but not necessary.

Technical skills:

• Strong proficiency in Python (required).
• At least 3 years of hands-on experience with deep learning, including model development, training, and optimization (required).
• Knowledge of popular deep learning frameworks such as Tensorflow and PyTorch (required).
• Familiarity with popular bioinformatics tools (e.g., PyMol, and/or Chimera), and databases (e.g., PDB, UniProt) (desirable).

Soft skills:

• A research oriented and quantitative thinking attitude.
• Proven ability to work in interdisciplinary teams.
• Willingness to support and mentor younger scientists working in deep learning for drug discovery.
• Excellent writing and presentation skills.
• Fluent in spoken and written English (C1 level).

Conditions of Employment

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for 2 years.
• Salary in accordance with the Collective Labour Agreement for Dutch Universities, scale 10 (min. € 4,060 max. € 5,331).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs on general skills, didactics and topics related to research and valorization.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• Partially paid parental leave and an allowance for commuting, working from home and internet costs. 
• A TU/e Postdoc Association that helps you to build a stronger and broader academic and personal network, and offers tailored support, training and workshops.
• A Staff Immigration Team is available for international candidates, as are a tax compensation scheme (the 30% facility) and a compensation for moving expenses.

Information

Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Prof. Francesca Grisoni, f.grisoni@tue.nl

Visit our website for more information about the application process or the conditions of employment.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application

We invite you to submit a complete application using the apply-button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a full list of publications and conference contributions, and the contact information of three references.
• A list of 2 to 5 selected publications, along with a summary of their content, a description of their relevance for the scopes of the project, your role in the research, and the corresponding DOIs. Preprints and conference papers can be included.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled. Please note that applications via email will not be considered.