<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=us-ascii">
</head>
<body style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;">
<div style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;">
Dear all,
<div><br>
</div>
<div>We have a 3-year PostDoc position in the area of Causal Machine Learning and Reinforcement Learning at the Vrije Universiteit Amsterdam.</div>
<div><br>
</div>
<div>The position focuses both on fundamental contributions in those areas, but also applications in healthcare. More specifically, the position is embedded in two projects which act as application domains. First of all, the ten-year gravitation grant Stress
in Action, funded through NWO (Dutch National Science Foundation). The goal of the project is to move stress research from the lab into daily life, and hence, the use cases of the methodological innovations will focus on applications to stress-related data,
such as wearables, ecological momentary assessments, and other types of questionnaires. Secondly, the ZonMW funded MINMED project which aims to unlock causal effects of interventions in elderly care from observational data. </div>
<div>
<div><br>
</div>
<div>A variety of academic partners are involved in the two projects, including Vrije Universiteit Amsterdam, Amsterdam UMC, Erasmus MC, University of Twente, University of Groningen, UMC Groningen, and Utrecht University. The position is embedded in the Quantitative
Data Analytics (QDA) group of the VU in close collaboration with the Amsterdam UMC, Erasmus MC and the University of Groningen. The QDA group focuses on both fundamental and application-driven research in ML.</div>
</div>
<div><br>
</div>
<div>For more information please follow the link below, the application deadline is 27 September 2026.<br>
<div><br>
</div>
<div><a href="https://workingat.vu.nl/vacancies/postdoc-in-causal-machine-learning-and-reinforcement-learning-3-years-amsterdam-1274527">https://workingat.vu.nl/vacancies/postdoc-in-causal-machine-learning-and-reinforcement-learning-3-years-amsterdam-1274527</a></div>
<div><br>
</div>
<div>Best regards,</div>
<div><br>
</div>
<div>Mark
<div>
<p class="MsoNormal"><a name="_MailAutoSig"><span lang="EN-US" style="font-size: 7.5pt; font-family: Arial, sans-serif; color: rgb(91, 91, 91);">-----<o:p></o:p></span></a></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size: 7.5pt; font-family: Arial, sans-serif; color: rgb(91, 91, 91);">Mark Hoogendoorn <br>
<br>
Full Professor of Artificial Intelligence <br>
Chair Quantitative Data Analytics Group <br>
<br>
</span><span lang="EN-US" style="font-size: 7.5pt; font-family: Arial, sans-serif; color: rgb(0, 137, 207);">Vrije Universiteit Amsterdam <br>
Faculty of Science, Department of Computer Science </span><span lang="EN-US"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size: 7.5pt; font-family: Arial, sans-serif; color: rgb(91, 91, 91);">T +31 20 59 87772 <br>
E </span><a href="mailto:m.hoogendoorn@vu.nl" target="notSet"><span lang="EN-US" style="font-size: 7.5pt; font-family: Arial, sans-serif; color: rgb(24, 137, 207);">m.hoogendoorn@vu.nl</span></a><span lang="EN-US" style="font-size: 7.5pt; font-family: Arial, sans-serif; color: rgb(91, 91, 91);"> |
URL </span><a href="http://www.cs.vu.nl/~mhoogen/" target="notSet"><span lang="EN-US" style="font-size: 7.5pt; font-family: Arial, sans-serif; color: rgb(24, 137, 207);">www.cs.vu.nl/~mhoogen/</span></a><span lang="EN-US" style="font-size: 7.5pt; font-family: Arial, sans-serif; color: rgb(91, 91, 91);"><br>
MAILING ADDRESS: De Boelelaan 1111, 1081 HV Amsterdam</span><span lang="EN-US" style="font-size: 7.5pt;"> </span><span lang="EN-US" style="font-size: 7.5pt; font-family: Arial, sans-serif; color: rgb(91, 91, 91);"><br>
VISITING ADDRESS: NU-10A87 </span></p>
</div>
</div>
</div>
<div></div>
<br>
</div>
</body>
</html>