[DL] Two career track assistant/associate professor positions @ VU Amsterdam

[Hoogendoorn, M. (Mark)]

Dear all,

VU Amsterdam has two vacancies for a career track assistant/associate professor related to Artificial Intelligence (with an application deadline on November 5th):

Assistant/associate professor in AI & Health
The potential of techniques from Artificial Intelligence for improved patient care is widely recognized. However, the number of applications that make it to the patient or clinician remains low. One of the causes of this gap is that clinicians and AI experts often speak a different language. To try and bridge the gap between the two disciplines the Amsterdam UMC (AUMC) and Vrije Universiteit Amsterdam (VU) are joining forces and are creating a joint position between the Cancer Center Amsterdam of the Amsterdam UMC and the Department of Computer Science at the Vrije Universiteit Amsterdam.

The position will focus on the use and re-use of structured and semi-structured clinical data (opposed to medical imaging or bioinformatics) to deploy and improve machine learning techniques to develop clinically relevant models, mainly (but not exclusively) targeting predictive modeling and personalization of healthcare. Besides purely data-driven approaches, making a combination with the vast amount of domain knowledge present in the medical domain is also in scope.

For more details, see https://workingat.vu.nl/ad/assistant-associate-professor-in-ai-health/wglx34

Assistant/associate professor in Human-Aware AI
Algorithms are pervading society at a rapid pace. They are used in a variety of contexts, ranging from the replacement of certain tasks humans prefer to offload or cannot handle at large scale, to systems that support or advise humans. With the advent of these systems, their downsides also become more and more prominent. Systems that do not treat certain groups fairly and include biases, for example, have a huge impact on society. We are looking for an assistant/associate professor that focuses on algorithmic solutions for these problems. Examples of such adaptive, responsible and explainable AI may include learning bias-free models from biased data, evaluation approaches to estimate algorithmic fairness, formal norms and constraints on algorithms to guarantee fair treatment, culturally inclusive- and socially-aware AI, or explainable AI methods, as well as other relevant algorithmic approaches and solutions.

For more details, see https://workingat.vu.nl/ad/assistant-associate-professor-tenure-track-in-human-aware-artificial-intelligen/7supvw

Best regards,

Mark
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Mark Hoogendoorn

Full Professor of Artificial Intelligence
Chair Quantitative Data Analytics Group

Vrije Universiteit Amsterdam
Faculty of Science, Department of Computer Science
T +31 20 59 87772 | M +31 6 539 22626
E m.hoogendoorn at vu.nl<mailto:m.hoogendoorn at vu.nl> | URL  www.cs.vu.nl/~mhoogen/<http://www.cs.vu.nl/~mhoogen/>
MAILING ADDRESS: De Boelelaan 1111, 1081 HV Amsterdam
VISITING ADDRESS: NU-10A87

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