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<p>At the Department of Computer Science of the Vrije Universiteit
Amsterdam we have two new tenure track positions available in the
domain of AI. The application deadline is April 30th for both
positions. Please find a brief description of the positions below
including a link to a more detailed vacancy description.<br>
</p>
<p><b>Assistant Professor in Machine Learning (tenure track)<br>
</b></p>
<p>We are looking for a new assistant professor who will
collaboratively contribute to research and teaching in the area of
machine learning (ML). The position is embedded in the
Quantitative Data Analytics group. The group focuses on both
fundamental and application-driven research in ML. We are looking
for candidates with experience in the area of machine learning,
with a special preference for those having expertise in one or
more of the following areas: data-efficient ML methods,
explainability of ML methods, and the utilization of domain
knowledge in ML. We are interested in attracting an active
researcher, able to perform ground-breaking research and to apply
this research in relevant societal domains, including
health-related analytics. On top, the candidate should be
passionate about teaching.<br>
</p>
<p>For more details, see <a class="moz-txt-link-freetext"
href="https://workingat.vu.nl/ad/tenure-track-assistant-professor-machine-learning/8kur3v"
moz-do-not-send="true">https://workingat.vu.nl/ad/tenure-track-assistant-professor-machine-learning/8kur3v</a>
<br>
</p>
<p><b>Assistant or Associate Professor in AI & Health (tenure
track)<br>
</b></p>
<p>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.<br>
<br>
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.<br>
<br>
We are looking for a colleague with a cutting expertise to
maintain our stream of high quality publications in this area,
acquire external research grants, conduct excellent teaching, and
act as a bridge builder between the two involved institutes.<br>
</p>
<p>For more details, see <a class="moz-txt-link-freetext"
href="https://werkenbij.vu.nl/ad/assistant-associate-professor-in-ai-and-health-f-m/zxjo0t"
moz-do-not-send="true">https://werkenbij.vu.nl/ad/assistant-associate-professor-in-ai-and-health-f-m/zxjo0t</a></p>
<p>Best regards,</p>
<p>Mark<br>
</p>
<p>---</p>
<p class="MsoNormal"> <span
style="font-size:7.5pt;font-family:"Arial",sans-serif;color:#5B5B5B">
Mark Hoogendoorn <br>
<br>
Full Professor of Artificial Intelligence <br>
Chair Quantitative Data Analytics Group <br>
<br>
</span> <span
style="font-size:7.5pt;font-family:"Arial",sans-serif;color:#0089CF">
Vrije Universiteit Amsterdam <br>
Faculty of Science, Department of Computer Science </span> </p>
<p class="MsoNormal"><span
style="font-size:7.5pt;font-family:"Arial",sans-serif;color:#5B5B5B">
T +31 20 59 87772 | M +31 6 539 22626 <br>
E <a href="mailto:m.hoogendoorn@vu.nl" target="notSet"
moz-do-not-send="true"><span style="color:#1889CF">m.hoogendoorn@vu.nl</span></a> |
URL <a href="http://www.cs.vu.nl/~mhoogen/" target="notSet"
moz-do-not-send="true"><span style="color:#1889CF">www.cs.vu.nl/~mhoogen/</span></a><br>
MAILING ADDRESS: De Boelelaan 1111, 1081 HV Amsterdam</span><span
style="font-size:7.5pt;font-family:"Lucida
Grande",sans-serif;color:#5B5B5B"> </span><span
style="font-size:7.5pt;font-family:"Arial",sans-serif;color:#5B5B5B"><br>
VISITING ADDRESS: NU-10A87 </span></p>
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