PhD on AI-Empowered Physical-Digital Twins for Designing Bio-Digital Devices

Are you excited at the prospect of becoming an expert in the emerging field of bio-digital devices? Are you eager to investigate the potential of digital twin technologies to transform the way that designers create bio-digital products? Do you want to work at the intersection of AI, electronics and biology, and have a foundation in data-driven solutions? Then this could be the opportunity you've been waiting for - We are seeking an enthusiastic and self-driven graduate student to join our team!

Job Description

This project focuses on designing and developing advanced AI-empowered systems that integrate physical and digital technologies to support the creation of bio-digital devices. These may include adaptive incubators for premature babies, life support systems, and other devices that interact with living organisms. The project focuses on digital twins of biological processes, integrating biomechanical and biochemical data into a platform that can support designers in designing bio-digital devices. These digital twins can support product designers with dynamic feedback to simulate and analyze the interaction between product and biological systems in the early stages of the product design process. Eventually this may improve their safety, function and usability and the efficiency of the development process.

You will develop a framework and platform with associated physical and digital tools for allowing knowledge from computational biology to support the design of bio-digital devices.

To do so, you will:

1. Research and develop tools to support the integration of physical and digital systems with biological data.
2. Apply techniques from Artificial Intelligence to research, analyze, develop, implement, and evaluate algorithms, and models related to bio-digital device design.
3. Integrate data-driven and model-driven digital twins of biological systems with sensor- and actuator-enabled physical systems to simulate and evaluate interactions of bio-digital devices within a specific environment.

Requirements:

• A master's degree (or an equivalent university degree) in an area relating to (Computational) Biomedical Engineering, Mechanical Engineering, Computer Science, Human-Computer Interaction, or a closely related topic.
• Knowledgeable in system development, including front-end and back-end development. Familiar with AI techniques (e.g., machine learning, deep learning, predictive analytics) and data-driven approaches (e.g., data processing, data visualization, and data modeling).
• Experience with modelling biological processes.
• Motivation and ability to work in an interdisciplinary team including designers and healthcare professionals, to understand their needs, conduct co-design activities, and perform evaluation work.
• Familiarity with design thinking methodologies, academic writing and publishing scientific research, and collaborative research projects will weigh positively. Experience in integrating AI-based insights into the design process will be considered an advantage.
• Fluent in spoken and written English (C1 level).
• A research-oriented and open-minded attitude.

Salary Benefits:

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, scale P (min. €2.901,00 max. €3.707,00).
• 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, if applicable) for international candidates.

38 hours per week

De Rondom 70