We are seeking one Industrial Design PhD candidate for the Advancing Cancer Care with AI research project.

Project background

The Eindhoven MedTech Innovation Center (e/MTIC) is a public-private partnership aimed at creating and growing an ecosystem that offers a fast track to high-tech health innovations. Within this ecosystem, we aim to create impactful innovations in the oncology domain, through close multidisciplinary collaboration between an academic partner (Eindhoven University of Technology), top-clinical hospital (Catharina Hospital Eindhoven) and industrial partner (Philips Research and Philips Experience Design). Our specific focus of this project is to advance clinical decision support for (lung & pancreas) cancer care with artificial intelligence (AI), taking a patient-centered and physician-centered approach to optimize physician-AI collaboration and adoption of AI in clinical practice. This project builds on prior work that has been developed within e/MTIC in recent years.

This design PhD position is one of in total 4 PhD positions in this project. The project aims to a) iteratively define, build and validate how we can make AI algorithms 'ready' for real-world conditions under which they have to work in clinical practice, b) explore using a research-through-design approach what is needed (from AI and physician) for an optimal collaboration between the physician and the AI, and c) measure the holistic effect of the physician-AI collaboration solutions on adoption and use of AI in the field, i.e. appropriate use, impact on patient outcomes and physician experience. It is key to design human-centered AI solutions that encourage long-term use and trustworthy engagement, and that also focus on the patient and physicians as the central stakeholders.

You will be part of an innovative multi-disciplinary team

This design PhD position will be embedded in a multidisciplinary team of in total 4 PhD positions covering clinical, machine learning, and design expertise. The project activities are organized in 3 tightly interlinked work packages, of which work package 2 is led by this design PhD position.  

WP1. Machine Learning for robust & trustworthy AI

This activity, led by the machine learning PhD student, aims to develop robust and interpretable AI in medical imaging. It will address a subset of clinical application areas (e.g., lung cancer and pancreas cancer), by development and maturation of AI methods for the selected clinical use cases.

WP2. User experience and interface design and evaluation for optimal physician-AI collaboration

This activity, led by the design PhD student, aims to iteratively develop and evaluate UI/UX innovations to shape optimal physician-AI collaboration, as well as methods to evaluate the clinical experience with end-users. This will drive the AI models developed in WP1 and integrate AI-based outputs generated in WP1. This activity will investigate novel domain-specific quality criteria, methods and tools regarding AI integration in a clinical environment. These will be used in collaboration with WP3 to evaluate the impact of the solution on the clinical experience (e.g. trust in the AI solution and its recommendations) and outcomes (e.g. decision quality). More details of this position are provided below.

WP3: Clinical data collection, user testing and evaluation

In this activity, led by the two clinical PhD students, the AI algorithms developed in WP1, clinician-AI collaboration innovations developed in WP2 and the experience with AI will be evaluated in clinical practice through retrospective and semi-prospective clinical studies.

The 4 PhD candidates will closely collaborate and share data, AI models, technological platforms and methodologies as complementary focus points of each PhD position.  

Industrial Design PhD position: designing and evaluating optimal physician-AI collaboration

In the design-research trajectory, the PhD student will explore how to design and evaluate the optimal physician-AI collaboration. This can be achieved through design contributions to machine learning challenges, such as AI explainability, interpretability and uncertainty quantification, as well as user interface (UI) and user experience (UX) design challenges, such as how and when to show AI-generated findings, explanations and visualize uncertainty for professional end-users. In fact, designing optimal physician-AI collaboration is a combined data science and UI/UX design challenge and will be treated as such in this project.

We are interested in understanding what is the optimal envisioned collaboration between physician and AI to foster adoption and appropriate trust of AI in clinical practice. Important questions are:

• What are quality criteria for the optimal physician-AI collaboration? And how can these be measured and tested in an iterative process? (e.g., physician appropriately trusts/ relies on the AI, optimally adds value to clinician and patient, seamlessly fits in workflow, regulatory and ethics).
• How to design AI and user interfaces for optimal physician-AI collaboration, and which underlying generalizable principles explain this? This will manifest in iteratively creating and evaluating data-driven prototypes embodying the AI creating a seamless clinical workflow and trusted experience (e.g., using data visualizations, medical images, and 3D anatomical renderings).
• What tools do design & development teams need to iteratively design and evaluate physician-AI collaboration over time?

The PhD student will explore these questions by applying the research through design methodology with hands-on making and prototyping in close contact with prominent users of this system such as radiologists, clinicians and surgeons. These will be closely involved in the co-creation process.

Eindhoven University of Technology (TU/e, www.tue.nl) is one of Europe's leading research universities. The Eindhoven area, in the southern part of the Netherlands, is one of Europe's top 'innovation ecosystems', with many high-tech companies and institutes. TU/e is intertwined with many of these companies and institutes, and research at TU/e is characterized by a combination of academic excellence, industrial relevance and societal interweaving.  The Department of Industrial Design (ID) of the Eindhoven University of Technology (TU/e), founded in 2001, is a maturing department with over 650 students, both Bachelor and Master, and around 40 research staff members and about 10 lecturers. The mission of the department of Industrial Design at TU/e is Research on and Education in the Design of Systems with Emerging Technologies in a Societal Context.

The PhDs will be under the supervision of Prof. dr. Lin-Lin Chen and Dr. Mathias Funk in the Department of Industrial Design at Eindhoven University of Technology. The project will be executed in collaboration with Philips Experience Design; Dr. Jon Pluyter and Dr. Saskia Bakker of Philips Experience Design are closely involved in the supervision of the PhD students. At the TU/e, the positions are situated within the research cluster of 'Future Everyday'. The Future Everyday cluster investigates the everyday interactions between individual people and the highly interconnected technology that surrounds them. Researchers measure, model and design for the user experience when individuals interact with social-technological networks in their homes, at work, in transit, while doing sports or going out.

Prospective starting date: August 2021.

• A Masters degree in an industrial design related discipline (e.g., Industrial Design, Computer Graphics). Masters degree needs to be obtained before the prospective starting date of this position: August 2021.
• A design portfolio demonstrating skills and knowledge in contextual design exploration, digital fabrication and interactive prototyping (of AI-enabled solutions), user evaluation test design & execution skills.
• A commitment to research through design, reflection and co-design.
• Ability to conduct and deliver high quality research both independently and as part of an interdisciplinary team.
• Openness, interest and good soft skills to work closely with people from other disciplines and across organizations.
• Eager to learn and tackle complex healthcare challenges. Experience working in a healthcare (design) context is a plus.
• Good conceptual design skills for UI and data visualization.
• Hands-on programming skills for AI and data visualization. Knowledge and skills in Programming languages (e.g., Python, Java, JavaScript), Data Visualization Libraries and tools (e.g. D3, Processing), 3D digital models and visualization tools (e.g., Unity, Three.js), and eager to further develop these skills.
• Fluency in English is a must (written and spoken), Dutch (spoken) desirable.
• Eager to spend part of your time on-site with project partners (Philips, Catharina Hospital) to fully apprehend and profit from the expertise, capabilities and facilities of each partner (all partners are located in close proximity to each other).

• A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
• A full-time employment for four years, with an intermediate evaluation after one year.
• To support you during your PhD and to prepare you for the rest of your career, you will have free access to a personal development program for PhD students (PROOF program).
• A gross monthly salary and benefits in accordance with the Collective Labor Agreement for Dutch Universities.
• Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
• A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
• Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.