PhD on Scientific Machine Learning for Personalised Medicine and Precision Nutrition

Introduction

Scientific Machine Learning for Personalised Medicine and Precision Nutrition.

• Are you inspired by health care challenges?
• Are you eager to work on the development of cutting-edge modelling and AI approaches for personalised medicine?
• Are you our next PhD-candidate in scientific machine learning for precision nutrition?

Job Description

In recent years, artificial intelligence (AI) and machine learning (ML) have shown great potential in healthcare, particularly in oncology, where models have been trained to predict personalised treatment strategies based on different omics measurements and improved long-term patient outcomes. However, these models often require large datasets, limiting their application across other biomedical fields.

This PhD project aims to push the boundaries of AI in healthcare by exploring scientific machine learning—an emerging branch of AI that integrates existing scientific knowledge into machine learning algorithms, reducing the need for large datasets. In this project you will develop a framework combining mechanistic mathematical models with machine learning techniques to create hybrid models capable of integrating high-dimensional omics data (such as genomic or microbiome profiles) with time-series data on metabolomics and clinical parameters.

The project will focus on applying these hybrid modelling framework to data from human dietary intervention studies to explore the role of gut microbiome composition and chronic low-grade inflammation in the development of cardiometabolic diseases. You will also investigate how these models can predict individual responses to various dietary interventions, potentially transforming precision nutrition and personalised disease prevention strategies.

We are seeking motivated PhD candidates with a strong interest in machine learning, mathematical modelling,  and biomedical data analysis. This is an exciting opportunity to contribute to the development of next-generation AI tools in the biomedical field and make a significant impact on public health.

The position will be based at the Computational Biology groups in the Department of Biomedical Engineering under the supervision of dr. Shauna O’Donovan and Prof.dr.ir Natal van Riel. The Computational Biology Group consists of a multi-disciplinary team of researchers that work on developing novel computational approaches for digital twins and decision support systems in healthcare and the prediction of personalised treatments in the areas of cardiometabolic diseases and oncology.  In addition to the research described above, you will supervise MSc/BSc students that will work on projects within the scope of your research.

Job Requirements

• A master’s degree (or an equivalent university degree) in Biomedical Engineering, Systems Biology, Applied Mathematics, Bioinformatics or similar discipline.
• Experience with programming in Matlab, Julia or Python
• Previous experience in processing and analysing omics data is not a requirement but is a plus.
• A research-oriented attitude.
• Ability to work in an interdisciplinary team and interested in collaborating with industrial partners.
• Motivated to develop your teaching skills and coach students.
• Fluent in spoken and written English (C1 level).

Conditions of Employment

• 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: 
• Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment. 
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 2,901 max. € 3,707).  
• A year-end bonus of 8.3% and annual vacation pay of 8%. 
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process. 
• An excellent technical infrastructure, on-campus children's day care and sports facilities.  
• An allowance for commuting, working from home and internet costs. 
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates. 

Information

Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Shauna O’Donovan, Assistant Professor, s.d.odonovan@tue.nl or Natal van Riel, Full Professors, N.A.W.v.Riel@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@tue.nl.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application

We invite you to submit a complete application by using the apply button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references.
• List of courses and grades of your BSc and MSc degrees as transcripts.
• Pdf copy of your final MSc thesis (if available)

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.