PhD student position in AI-driven biomolecular engineering

Project description
It is estimated that ~75% of the human proteome lacks deep binding sites and is considered “undruggable” by traditional small molecule inhibitors. Nonetheless, these so-called undruggable targets are implicated in a wide range of diseases, including cancer, autoimmune diseases, and cardio-metabolomic diseases, motivating the development of therapeutic modalities beyond small molecule inhibitors. Deep generative models (DGMs) are poised to transform our approach to biomolecular engineering by designing molecules with desired properties from scratch so as to minimize experimental screening. Nonetheless, they have seen limited integration of high content assay data. DGMs not only enable scientists to delegate error-prone decisions to computers via the use of predictive and generative computational models, but also have the added advantage that they can learn from datasets of billions of molecules in minutes and be regularly updated with new data.

In this project, the candidate will focus on the development of novel AI tools, particularly deep generative models, for the controlled design of therapeutic modalities based on phenotypic profiles. The goal is to develop ML-based de novo design tools which enable researchers to reverse engineer novel bioactive molecules given a desired phenotype. To this end, the candidate will have the opportunity to work with a range of -omics datasets and high-content screening data, as well as to build on the latest developments in machine learning. While the focus of this project is on deep learning and method development, the ideal candidate will also have a keen interest in molecular biology.

Information about the division and the department
The AI Laboratory for Biomolecular Engineering (AIBE) is based in the Data Science & AI (DSAI) division in the Department of Computer Science and Engineering (CSE). Led by Dr. Rocío Mercado, our group uses methods from machine learning and the life sciences to understand how molecules interact to form complex systems, and how we can use these insights to engineer molecular systems for therapeutic applications. We are currently focused on applying our computational tools to improving the understanding and design of multi-target therapeutic modalities like PROTACs and molecular glues, which require large networks of proteins to come together and cooperate for the desired therapeutic effect to occur. We interact closely with leading academic and industrial groups in computational chemistry, bioinformatics, and computer science. In AIBE, we seek to create a vibrant and collaborative environment where students and postdocs are supported in their pursuit of challenging research questions at the forefront of machine learning and the life sciences.

The CSE department is a joint department at Chalmers University of Technology and the University of Gothenburg, with activities on two campuses in the city of Gothenburg. The department is divided into four divisions, and employs around 270 people from over 30 countries. Research in the department has a wide span, from theoretical foundations to applied systems development. We provide high quality education at the Bachelor's, Master's and graduate levels, offering over 120 courses each year. We also have extensive national and international collaborations with academia, industry and society.

Our aim is to actively improve our gender balance in both our department and division. We therefore strongly encourage applicants from historically-excluded groups to our positions, such as women and non-binary individuals. As an employee of Chalmers and CSE department, students are given the opportunity to contribute to our active work within the field of equality and diversity.

Major responsibilities
The major responsibilities for a PhD student position in the division include conducting doctoral research and coursework. By the end of the PhD, students will be able to identify novel research directions and design the appropriate computational experiments to answer key questions. Students are expected to effectively communicate the results of their research verbally and in writing, and will receive specific training towards building these skills. This position also includes teaching at Chalmers' undergraduate level, or performing other teaching duties corresponding to 20% of working hours.

Qualifications
To qualify as a PhD student, applicants must have a master's level degree corresponding to at least 240 higher education credits in Computer Science, Chemistry, Bioengineering, or a related field. Previous coursework in molecular biology would be beneficial but not required. The applicant should have strong background and experience in Python programming and deep learning. Previous experience in deep generative models, reinforcement learning, computer vision methods, or high-content screens would be a merit, but not required.

The position requires sound verbal and written communication skills in English. If Swedish is not your native language, 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 deadline: 28-02-2023

*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***