PhD in “Designing Human-AI Data Sensemaking for Collaborative Decision Making”

Updated: about 1 month ago
Deadline: 23 Dec 2022

Irène Curie Fellowship

No


Department(s)

Industrial Design


Reference number

V51.6099


Job description

Project Background

AI-empowered tools have shown great potential in supporting medical diagnosis in the healthcare domain; however, these tools have still hardly made impacts in real-world practice at this moment. To tackle these challenges, this project aims to develop new approaches and tools that enable designers to effectively harness large amounts of data to analyze complex real-world situations for supporting professional medical experts to make good decisions. Moreover, this project will explore the challenge of multiple stakeholders collaboration in which patients, medical experts with different knowledge and expertise and AI agents work together to understand, analyze and synthesize medical data in the process. In particular, we will design AI-empowered tools that support a clinical team to understand AI’s capabilities and limitations, cope with imperfect AI (e.g., ambiguous/difficult cases), and build trust relationships in collaboration with AI in a high-stakes decision-making process. With this project, we will contribute useful tools, framework and design guidelines for future human-AI collaboration in the context of clinical decision-making.

Industrial Design PhD position

In the design-research trajectory, this PhD student will explore how to design, develop and evaluate the human-AI collaboration for supporting clinical decision making. In particular, this PhD will explore how to incorporate AI into data sensemaking processes to facilitate multi-stakeholder collaboration in the context of clinical decision making. This can be achieved through design contributions to machine learning challenges (e.g., Machine teaching, AI explainability, transparency and uncertainty quantification) and user interface (UI) and user experience (UX) design challenges (e.g., how and when to show AI-generated questions, findings and explanations, appropriately visualize uncertainty and bias for professional end-users, and devise interactive interfaces for AI adoption). Designing effective collaborative data sensemaking is a combined data science, ML/AI and UI/UX design challenge; the PhD student will deal with these challenges in this project.

We are interested in understanding what is the envisioned collaboration between professional medical experts and AI for fostering adoption and appropriate trust of AI in clinical practice. The goal of this project is to gain new knowledge of how data sensemaking impacts clinical decision making and develop AI-powered tools for supporting professional decision making. The project will address critical challenges on various human-AI collaboration strategies on training AI, onboarding AI, communicating with AI and retraining AI.

We will explore key questions in the context of this project:

  • How can we design privacy-aware data collection and visual representation tools for clinical experts to provide optimal care?
  • How can we design appropriate interfaces that provide explainability and transparency for supporting clinicians to make better use of AI in their collaborative medical decision making?
  • How can we support clinicians to onboard AI for helping specific sub-tasks of clinical care (e.g., everyday behavior, movement and bio-signal detection, telemonitoring and discovering anomalies in remote care, comprehensive summaries of patient status, etc.)?
  • How can we design tools that support design & development teams to iteratively design and evaluate clinician-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 diverse stakeholders such as clinicians, patients and AI agents. These will be closely involved in the co-creation process.

About research group and university

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.

This project is funded by the Eindhoven AI System Institute (EAISI, https://www.tue.nl/en/research/institutes/eindhoven-artificial-intelligence-systems-institute/ ). The mission of EAISI is to support AI-related research and activities at TU/e. Top researchers from various research groups work together to create new and exciting AI applications with a direct impact on the real world. All this in close collaboration with student teams and representatives from industry.

About the supervision team

The PhD will be under the supervision of dr. Janet Yi-Ching Huang, dr. Mathias Funk and Prof. dr. Lin-Lin Chen in the Department of Industrial Design at Eindhoven University of Technology. Please contact dr. Huang for further details or questions (y.c.huang[at]tue.nl ). The project will be executed in collaboration with Philips Experience Design, e/MTC, and other institutes. At TU/e, the position is part of the ‘Future Everyday’ research cluster. 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: February 2023.


Job requirements
  • A Master’s degree in a related area of design (e.g., Industrial Design, Interaction Design, Data Visualization) or a related discipline (e.g., Computer Science) and demonstrated competences in one or more of these domains: Industrial Design, Interaction Design, AI, Human-Computer Interaction, Data visualization, Computer/Data science, and other relevant fields. The Master’s degree needs to be obtained before the prospective starting date of this position.
  • Skills and knowledge in contextual design exploration, digital fabrication and interactive prototyping (of AI-enabled solutions), user evaluation test design & execution skills, e.g., as shown by a design portfolio or exemplars.
  • Openness, interest and good soft skills to work closely with people from other disciplines and across organizations.
  • Ambition 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, and affinity with methods like Research-through-Design and co-design.
  • Interest in developing skills in conducting and delivering high quality research both independently and as part of an interdisciplinary team.
  • Hands-on programming skills for AI and data visualization, and ambition to further develop these skills. Such as programming languages (e.g., Python, Java, JavaScript), data visualization tools (e.g., D3.js, Processing), 3D digital modeling tools (e.g., Unity, Three.js), and basic AI/ML or data science knowledge and skills (e.g., ml5.js).
  • Excellent written and spoken English, in addition, Dutch language skills is a plus.

Conditions of employment
  • 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.

Information and application

Please contact dr. Huang for further details or questions (y.c.huang[at]tue.nl ).

Visit our website for more information about the application process or the conditions of employment. You can also contact HR Services,(HRServices.ID[at]tue.nl).

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

How to apply

Your application must contain the following documents (all in English):

  • A written application letter with a clear motivation section.
  • A portfolio.
  • A curriculum vitae.

Please note that a maximum of 5 documents of 2 MB each can be uploaded via the apply now button. If you have more than 5 documents you will have to combine them. Click here if you want to apply.

Applications by e-mail are not accepted.

The deadline for applications is 23 December 2022. However, if you are interested, we invite you to apply as soon as possible. Selection will begin immediately and continue until the position has been filled.


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