PhD Student Position in Generative models for Inverse Molecular Design

Description
Inverse molecular design is the process of generating molecules with bespoke properties. Examples include a drug binding a specific biological target or an enzyme with high thermal stability. As such, inverse molecular design is a holy grail of chemical and biological engineering. However, the space of possible compounds or protein sequences is enormous, which excludes explicit screening or discriminative approaches. Here we seek to build a generative AI system that leverages multi-scalar and multi-modal data to generate compounds conditioned on their target properties. The selected candidate will join an interdisciplinary team in their efforts to target ion-channel proteins to modulate their function to a possible therapeutic effect.

Machine learning provides new exciting new opportunities in the natural sciences such as physics, chemistry, and biology. Its potential application areas span from designing new drugs against multi-resistant pathogens and understanding the impact of gene defects on a protein's function to speeding up computer simulations to understand fundamental scientific phenomena and design optimal algorithms for near-term quantum computers. The path toward these applications can leverage the power of deep learning to represent and process high-dimensional data effectively and encode natural laws and symmetries.

The Artificial Intelligence and Machine Learning for the Natural Sciences (AIMLeNS) group (head: Simon Olsson) is an interdisciplinary team of about ten researchers focusing on developing AI and ML systems to address outstanding challenges in the natural sciences. The recruited Ph.D. student will integrate into the AIMLeNS group. You can read more about the group at https://www.cse.chalmers.se/~simonols/

The selected Ph.D. student will lead the development of generative AI systems for inverse molecular design. The method development will be driven through interaction with experimental/computational groups in structural biology (Gourdon, LU), electrophysiology (Liin, LiU), and molecular biophysics (Delemotte, KTH). The aim is to generate compounds that use multi-modal, multi-scalar information to create compounds that modulate ion-channel function to hopefully cure diseases associated with dysfunction. We have a rigorous plan for testing and validation involving all the groups mentioned above and in vivo experiments (Broberger, SU). The selected candidate will build on previous work from our group (1).

1) Romeo Atance, Viguera Diez, Engkvist, Olsson, Mercado, JCIM (2022) 62 (20), 4863-4872

Information about the project
The project takes place at the Chalmers University of Technology.
The student will pursue a Ph.D. in machine learning in Computer science and engineering at Chalmers.

As a Ph.D. student in this project, you will join an interdisciplinary team with world-leading expertise in structural biology, machine learning, computational biophysics, electrophysiology, and neuroscience distributed across the top universities in Sweden: Chalmers, KTH, Stockholm, Linköping, and Lund universities. One goal unites the team: understand ion-channel protein function to better design compounds to modulate their function and address disorders such as epilepsies, cardiac arrhythmias, and muscular paralysis. A Kunt and Alice Wallenberg Foundation project grant funds the teams' efforts.

Major responsibilities
As a Ph.D. student, you will enroll in a graduate program at the Department of Computer Science and Engineering, where your primary responsibility is to pursue your doctoral studies, which entails:
• 80% Research and course work
• 20% Service, including teaching.
The research entails developing and implementing your scientific ideas, communicating your results orally or in written form. Service entails being a teaching assistant in Chalmers' undergraduate and masters-level courses or performing other departmental tasks.

Qualifications
To qualify as a PhD student, you must have a master's-level degree, or a four-year bachelor's degree, corresponding to at least 240 higher education credits in a relevant field. The degree should have been awarded at the latest at the time of start of the position. The position requires sound verbal and written communication skills in English. If Swedish is not your native language, you should be able to teach in Swedish after two years. Chalmers offers Swedish courses.

Contract terms
Full-time temporary employment. The position is limited to a maximum of five years.

We offer
Chalmers offers a cultivating and inspiring working environment in the coastal city of Gothenburg. 
Read more about working at Chalmers and our benefits for employees.

Chalmers aims to actively improve our gender balance. We work broadly with equality projects, for example the GENIE Initiative on gender equality for excellence. Equality and diversity are substantial foundations in all activities at Chalmers.

Application procedure
Follow link to Chalmers webpage where you find the add and details on application procedure: PhD Student Position in Generative models for Inverse Molecular Design