Postdoc in AI for protein representation learning in drug discovery

Updated: 21 days ago
Deadline: 31 Mar 2024


(Post-doctoral) Researcher

Irène Curie Fellowship



Biomedical Engineering

Reference number


Job description

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 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 ligand-based AI, as well as in medicinal chemistry and chemical biology.
  • Mentoring and supervising junior researchers and students who are working on AI-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 AI, chemistry, and biology, with a proactive and interdisciplinary attitude. You will become a member of the Molecular Machine Learning team (led by Dr. F. Grisoni), whose mission is to augment human intelligence in drug discovery with novel AI technology. You will also be embedded in the Chemical Biology group, the Dept. of Biomedical Engineering, the Institute for Complex Molecular Systems, and the Eindhoven AI Systems Institute, which are characterized by a highly interdisciplinary and collaborative approach to science and research.

Job requirements


  • A PhD degree (or an equivalent university degree) in Computer Sciences, Computer Engineering, Bioinformatics, or related disciplines.
  • Previous experience of deep learning, preferably applied to chemistry, biology, and/or healthcare.
  • Basic understanding of molecular biology and/or medicinal chemistry.

Technical skills:

  • Excellent knowledge of Python (required).
  • Previous in-depth experience with deep learning (required).
  • Knowledge of popular deep learning frameworks such as Tensorflow or PyTorch (required).
  • Experience with popular bioinformatics software, such as PyMol, and/or Chimera, and popular bioinformatics repositories, such as PDB and/or 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 AI 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 3 years.
  • Salary in accordance with the Collective Labour Agreement for Dutch Universities, scale 10 (monthly salary gross min. € 3.877,- and max. € 5.090,-).
  • 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 and application

About us

Eindhoven University of Technology  is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow. 


Do you recognize yourself in this profile and would you like to know more?
Please contact dr. Francesca Grisoni, f.grisoni[at]

Visit our website for more information about the application process or the conditions of employment. You can also contact Sascha Sanchez, HR advisor, s.j.m.g.sanchez.van.oort[at] or +31 40 247 7310.

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


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.

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