We are seeking a highly motivated candidate for a PostDoc position focused on visual analytics for explainable and trustworthy AI for risk assessment in healthcare.

This position is part of the SmartCHANGE (www.smart-change.eu) Horizon-Europe Research & Innovation project whose overall goal is to develop trustworthy AI-based decision-support tools to help health professionals and citizens reduce long-term risk of non- communicable chronic diseases (NCDs). The aim is to accurately assessing the risk of children and youth, including those with difficult-to-detect risks, and promoting the delivery of optimized risk-lowering strategies.

The postdoc will address the human-in-the-loop aspects for model self-auditing, and prediction understanding through visual analytics. The methods will aim at model understanding by machine-learning experts and health professionals. Visual analytics solutions will develop around the concept of counterfactuals to support bias identification, uncertainty estimation, and analysis of predictive and prescriptive model results. One of the main challenges will be to develop these solutions in the context of missing and heterogeneous data.

It is expected to develop prototypes based on the proposed methods following a suitable visual design process. The evaluation will be performed in collaboration with other members of the SmartChange consortium following, e.g., co-creation design approaches.

It is expected that the Postdoc will also play a relevant role in the organization and coordination of the project with the different members of the consortium and stakeholders.

The project will be developed within the visualization cluster under the supervision of Prof. Anna Vilanova (a.vilanova[at]tue.nl) and in strong collaboration with the Data and Artificial Intelligence cluster specifically Prof. Mykola Pechenizkiy group.

The visualization cluster (https://research.tue.nl/en/organisations/visualization) at TU/e has a strong track record in visualization and visual analytics for ML models and high- dimensional data. It has generated several award winning contributions at major visualization conferences (IEEE VIS, IEEE InfoVis, IEEE VAST, EuroVis); several successful start-up companies (MagnaView, Process Gold and SynerScope); and a number of techniques that are used on a large scale world-wide.

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

• You are enthusiastic about research in visual analytics, explainable AI, human-in-the- loop solutions in the healthcare context.
• You have a PhD in visual analytics ideally in relation to explainable AI and/or healthcare context.
• You have good communication skills, organizational and are able to work in a multidisciplinary team.
• You have strong programming skills (e.g., C++, Python,…).
• You are creative, critical, analytical, motivated, and persistent.
• You have a good command of the English language (knowledge of Dutch is not required, although willingness to learn is highly appreciated).

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 3 years.
• Salary in accordance with the Collective Labour Agreement for Dutch Universities, scale 10 (min. €3,877 max. €5,090).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs on general skills, didactics and topics related to research and valorization.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• Partially paid parental leave and an allowance for commuting, working from home and internet costs.
• A TU/e Postdoc Association that helps you to build a stronger and broader academic and personal network, and offers tailored support, training and workshops.

A Staff Immigration Team is available for international candidates, as are a tax compensation scheme (the 30% facility) and a compensation for moving expenses.