PhD student position in Machine Learning for Causal Inference

Information about the project
The data science and AI division at CSE is recruiting a PhD student for a project on Machine Learning for Causal Inference from Observational Data with Applications in Healthcare.

Many exciting applications of machine learning (ML) are found in medicine. Its potential use cases include diagnostics, treatment planning and understanding disease mechanisms. Notably, causality is a critical component in all of these problems: What is the underlying cause for symptoms? Will a change in treatment cause a beneficial effect? What genes increase the likelihood of developing a disease? These questions cannot always be answered through experimentation—as such experiments are often strictly regulated and sometimes infeasible—but must be addressed using observational data from the healthcare system, patient registries or biobanks.

In this project, we will study evaluation of sequential decision-making policies using observational data. This topic, also known as off-policy evaluation, is critical in many real-world applications, such as the continuous treatment of patients with chronic diseases. A key challenge in solving this problem is high dimensionality. The longer the sequences of decisions are, the more difficult it is to assess the impact of decisions made early in the sequence. Similarly, if the basis for decisions includes a large number of variables, finding two observations in contexts comparable across all variables quickly becomes infeasible. For this reason, it is of utmost importance to compress or represent these data in intelligent ways. In particular, the only data required for learning optimal policies, or evaluating them, are variables that were causal of the observed treatment and outcomes. This project aims to develop algorithms and theory for learning such representations, in a manner that preserves conditions for causal identification and ensures interpretability by domain experts.

The project is a collaboration between Chalmers University of Technology, Uppsala University, and AstraZeneca. The student will pursue a PhD in machine learning within computer science and engineering at Chalmers and will be funded though a collaboration grant from the WASP program (described below).

Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems.

The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish industry. Read more: https://wasp-sweden.org/

The graduate school within WASP is dedicated to provide the skills needed to analyze, develop, and contribute to the interdisciplinary area of artificial intelligence, autonomous systems and software. Through an ambitious program with research visits, partner universities, and visiting lecturers, the graduate school actively supports forming a strong multi-disciplinary and international professional network between PhD-students, researchers and industry. Read more: https://wasp-sweden.org/graduate-school/ 

Major responsibilities
Your major responsibilities as a PhD student is to pursue your own doctoral studies. You will be enrolled in a graduate program in the Department of Computer Science and Engineering. You are expected to develop your own ideas and communicate scientific results orally as well as in written form. In addition, the position will include 20% departmental work, mostly teaching duties in Chalmers' undergraduate and masters-level courses or performing other duties corresponding to 20% of working hours.

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

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 computer science, mathematics, signal processing, physics or related fields and experience in machine learning. The position requires sound verbal and written communication skills in Swedish and English. If Swedish is not your native language, you should be able to teach in Swedish after two years. Chalmers offers Swedish courses.

Application deadline: 30th June, 2020
First day of employment: 1st January, 2021 

>> APPLY HERE

For questions, please contact:
Fredrik Johansson, CSE DSAI
E-mail: fredrik.johansson@chalmers.se
Phone: + 46 (0)735 91 71 01

Chalmers continuously strives to be an attractive employer. Equality and diversity are substantial foundations in all activities at Chalmers.

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