PhD student Position in Digital Health for Synthetic Data in Health Care

The Biomedical signals and systems research group at the Department of Electrical Engineering is recruiting a qualified candidate for a PhD student position.

In this role you will join a research group that provides a stimulating, pleasant and flexible work environment for developing research and teaching, with a network reaching companies and health care representatives with special interest in Digital Health!

About the position
The digitalization of health care is an ongoing revolution that provides totally new possibilities to develop intelligent solutions promoting individualized and more equal care regardless of gender, ethnicity or geographical localization. The society is in the beginning of a large societal transformation of healthcare where more and more care will be provided in homes - supported by mobile care teams and Digital Health in many facets. At the same time more specialized care, for instance for acute diseases, will be centralized to specific hospitals, typically university hospitals. Both trends put a strong demand on qualified clinical decision support tools for those that act in the care front-line, like mobile teams and ambulances. The disease panorama will be very wide, early decisions very important for the patients and their medical outcome, and there is no chance of being expert or having experience and understanding of all types of cases being presented.

There is a shortage of large-scale clinical datasets that can be used in the development of these decision support solutions. This PhD position is committed to develop new methods to synthetically generate realistic health data using e.g. clinical knowledge and facts, statistics and machine learning. Such synthetic health data could speed up and improve the innovation of AI in healthcare and facilitate a more individualized and equal care.

This position aims to develop a better and more cost-effective, equal health care using digital solutions including decision support based on AI. The position is also part of a strategic investment to develop and expand the Digital Health research and innovation activities at our department. In our Digital Health group, we focus on developing clinical decision support (CDS) tools using e.g. AI to support informed clinical decisions and the transformation of healthcare. Our aim is to increase decision precision in crucial clinical decisions in the addressed care chains with the long-term goal to decrease mortality and suffering from major public health problems such as trauma, stroke, cardiac disease and falls. 

Synthetic health data generation has a wide range of use cases including simulation and prediction research (see recent review by Gonzales et al: https://doi.org/10.1371/journal.pdig.0000082 ). Popular methods are Generative Adversarial Networks (GAN) and federated learning. Some open-source software packages have been released, like Synthea that creates synthetic patients simulated from cradle to grave and has made a million synthetic patient records freely available ( https://synthea.mitre.org/ ), or HALO that is capable of generating high-fidelity data while protecting patient's privacy ( https://dx.doi.org/10.1038/s41467-023-41093-0 ). Considering the early phase of research about synthetic health data, Chalmers and the Kontiki project has the possibility to make a significant impact in this area, by establishing this PhD position.
 
The core team is the multidisciplinary network that exists in Digital Health research, development and innovation in Region Västra Götaland, reinforced by several companies and the City of Gothenburg.

The group also conducts research in bone-conduction hearing with applications, including for hearing aids, hearing examination and vertigo diagnosis as well as investigating movement in humans and animal models that include analysis of kinematics and signals recorded from muscles (EMG).

Major responsibilities
In this PhD student position you will develop new methods for synthetic data generation (SDG) in health care. Your research area will cover topics like AI, statistics, health data standards, and clinical research on target patient groups like trauma, stroke and frail elderly.

Specifically, you will contribute to the development of an SDG platform through the following three activities:

- Lay the theoretical foundation for the generic SDG platform, i.e. define, evaluate and design how synthetic data can be generated to fulfill the requirements for the different purposes the data will be used

- Take part in the hardware and software development for the platform.

- Scientific dissemination via journal articles and conference publications.

Besides research, the position generally also includes teaching on Chalmers' undergraduate and master level corresponding to about 20 per cent of working hours. Chalmers started a new Master of Science in Biomedical Engineering programme 2020, and has a master programme in Biomedical Engineering since around 2007.

Qualifications
To qualify as a PhD student, you must have a master's level degree corresponding to at least 240 higher education credits in a relevant field. 

Good verbal and written communication skills in both Swedish and English are required, and good interpersonal skills are needed. If Swedish is not your native language, you will need to be able to develop basic Swedish skills for facilitating project communication. Chalmers offers Swedish courses.

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

For more information about what we offer and the application procedure, please visit chalmers Web page.
See link: PhD student Position in Digital Health for Synthetic Data in Health Care