Artificial intelligence (AI) has the potential to revolutionize the field of drug discovery. By analyzing datasets of biological and chemical information, AI algorithms can identify patterns and relationships that may not be apparent to human researchers. AI can be used to aid in the design of new drugs, by predicting the likely biological activity of potential compounds. This can save time and resources by allowing researchers to focus on the most promising candidates. In addition, AI can be used to study the complex interactions between drugs and biological systems, leading to a better understanding of how drugs work and how they can be improved.
Did you guess that the text above was automatically generated with AI1) ? No? This showcases what deep learning can achieve. However, while the ‘artificial intelligence revolution’ is reshaping natural language processing, its potential is still untapped when it comes to drug discovery. Surely deep learning has accelerated tasks like synthesis prediction and molecule design, but we are still lacking methods to efficiently chart the vast ‘chemical universe’ and efficiently discover drugs for old and new diseases. These aspects provide an exciting opportunity to rethink current approaches for AI-driven drug discovery.
1) See openai.com/blog/chatgpt to know more!
This PhD vacancy is part of an ERC-funded project, which aims to advance the potential of AI to discover new drugs, by providing innovative ways of representing – and learning from – molecular information with AI. The project will be fueled by methodological innovation and aimed to discover novel bioactive molecules, faster. Moreover, the novel approaches that you will develop will be applied prospectively in the wet lab thereby providing a unique opportunity to validate the AI predictions in a real-world setting.
Your tasks will include:
Your work will lie at the interface between AI, chemistry, and biology, and it will be propelled by creative and interdisciplinary thinking. 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 innovation in AI. You will be embedded in the Chemical Biology group, the Dept. of Biomedical Engineering, and the Institute for Complex Molecular Systems, which are characterized by a highly interdisciplinary and collaborative approach to science.
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:
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]tue.nl.
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]tue.nl or +31 40 247 73 10.
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 by using the apply button. The application should include a:
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.