Project description

The integrity of biological tissues is actively maintained by cells. Applicable knowledge about how cells do this is of crucial importance to understand tissue diseases and to develop preventive treatment. The CELLSYSTEMICS project, which this PhD position is part of, aims to tackle these challenges in the clinical context of ascending aortic aneurysm. The core challenge is to tackle the complexity of the system of interrelated mechanisms within cells. This requires a structured identification framework, which will be developed in this PhD position.

This PhD project aims to uniquely and comprehensively characterize the cell mechanobiology at the intra-, inter-cell, as well as cell-matrix levels by using existing state-of-the-art tools and by further developing the theory and the algorithms based on novel system identification and data-driven modelling approaches. The envisioned system identification framework is aimed to be developed for the investigation and exploitation of cellular system dynamics from a control systems perspective. A bottom-up approach will be followed, focusing on capturing (intra)cell-level dynamics before cell-to-cell and cell-to-matrix dynamic models are developed.

Tasks

• Study the literature of modeling, machine learning, and (nonlinear / networked) system identification.
• Development of interpretable, data-driven (nonlinear / networked) system identification theory and algorithms for characterization of cell dynamics.
• Stochastic analysis of consistency and convergence of the results and empirical validation of the techniques on obtained data sequences.
• Exploration of the steps of the identification cycle for the developed methods from experiment design to verification (validation).
• Dissemination of the results of your research in international and peer-reviewed journals and conferences.
• Writing a successful dissertation based on the developed research and defending it.
• Assume educational tasks like the supervision of Master students and internships.
• Successful integration in the CELLSYSTEMICS project partner network (academical partners: Eindhoven University of Technology and Maastricht University, The Netherlands).

We are looking for a candidate who meets the following requirements:

• You are a talented and enthusiastic young researcher.
• You have experience with or a background in systems and control, mathematics, statistics, and signal processing. Ideally, you have experience with system identification and/or data-driven modelling.
• Preferably you finished a master's in Systems and Control, Biomedical Engineering, Mechanical or Electrical Engineering, (Applied) Physics or (Applied) Mathematics.
• You work well in a team with mixed expertise, with an interest towards biomedical applications.
• You have good programming skills and experience (Matlab and Python are an asset).
• You have good communicative skills, and the attitude to partake successfully in the work of a research team.
• You are creative and ambitious, hard-working, and persistent.
• You have good command of the English language (knowledge of Dutch is not required).

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 evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
• 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.
• 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.