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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">Subject:
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<td>[Ieee_vis_open_positions] PhD Position in Visual
Analytics at Aarhus University</td>
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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">Date: </th>
<td>Tue, 27 Aug 2019 10:28:57 +0000</td>
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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">From: </th>
<td>Hans-Jörg Schulz via ieee_vis_open_positions
<a class="moz-txt-link-rfc2396E" href="mailto:ieee_vis_open_positions@listserv.uni-tuebingen.de"><ieee_vis_open_positions@listserv.uni-tuebingen.de></a></td>
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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">Reply-To:
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<td>Hans-Jörg Schulz <a class="moz-txt-link-rfc2396E" href="mailto:hjschulz@cs.au.dk"><hjschulz@cs.au.dk></a></td>
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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">To: </th>
<td><a class="moz-txt-link-abbreviated" href="mailto:ieee_vis_open_positions@listserv.uni-tuebingen.de">ieee_vis_open_positions@listserv.uni-tuebingen.de</a>
<a class="moz-txt-link-rfc2396E" href="mailto:ieee_vis_open_positions@listserv.uni-tuebingen.de"><ieee_vis_open_positions@listserv.uni-tuebingen.de></a></td>
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<p class="MsoNormal">Applications are invited for a PhD
fellowship/scholarship at Graduate School of Science and
Technology, Aarhus University, Denmark, within the Computer
Science program. The position is available from 1 February
2020.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><b>Topic: Visualization of Knowledge Graphs
for Validation, Modification, and Optimization<o:p></o:p></b></p>
<p class="MsoNormal"><b><o:p> </o:p></b></p>
<p class="MsoNormal"><b>Apply here: <a
href="http://phd.scitech.au.dk/for-applicants/apply-here/november-2019/visualization-of-knowledge-graphs-for-validation-modification-and-optimization/"
moz-do-not-send="true">
http://phd.scitech.au.dk/for-applicants/apply-here/november-2019/visualization-of-knowledge-graphs-for-validation-modification-and-optimization/</a><o:p></o:p></b></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><b>Research area and project description:<o:p></o:p></b></p>
<p class="MsoNormal">Machine learning methods generate models
from training datasets. In many cases, these models are
obscure and incomprehensible to the human user – who, as a
result, remains unsure about what the models encode and
whether to trust their predictions. While some uncertainty
about their inner functioning may be acceptable when telling
dog pictures from cat pictures, in other applications like
medicine, autonomous driving, or air traffic control, it is
not. For these applications, visualization holds the promise
to play an important role in making machine learning results
more transparent, traceable, and predictable.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">This PhD project sets out to research novel
visualization methods for a particular type of machine
learning result – so-called Knowledge Graphs. Within an
interdisciplinary research project, these graph
representations are generated to capture workflows and their
relevant context information in hospitals. It will be your
task to first and foremost develop visual-interactive
techniques to communicate these knowledge graphs to medical
experts, so that they can validate and modify these graphs if
necessary. Furthermore, you are to explore the possibility of
using the resulting visualization as a means for monitoring
and optimizing healthcare workflows in hospitals.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Research questions to pursue in this
project are:<o:p></o:p></p>
<p class="MsoNormal"><b><o:p> </o:p></b></p>
<p class="MsoListParagraph"
style="text-indent:-.25in;mso-list:l0 level1 lfo1"><!--[if !supportLists]--><span
style="font-family:Symbol"><span style="mso-list:Ignore">·<span
style="font:7.0pt "Times New Roman"">
</span></span></span><!--[endif]-->How to show the learned
knowledge graph in a way that aligns with the mental map
medical doctors have about their hospital’s workflows? In
which ways do user preferences and professional background, as
well as the task at hand influence this display?<o:p></o:p></p>
<p class="MsoListParagraph"
style="text-indent:-.25in;mso-list:l0 level1 lfo1"><!--[if !supportLists]--><span
style="font-family:Symbol"><span style="mso-list:Ignore">·<span
style="font:7.0pt "Times New Roman"">
</span></span></span><!--[endif]-->What are good starting
points for manual modifications of the learned knowledge
graph? (e.g., circular or contradicting procedures within the
same workflow) How to support manual editing of knowledge
graphs by showing its implications in a What-If manner?<o:p></o:p></p>
<p class="MsoListParagraph"
style="text-indent:-.25in;mso-list:l0 level1 lfo1"><!--[if !supportLists]--><span
style="font-family:Symbol"><span style="mso-list:Ignore">·<span
style="font:7.0pt "Times New Roman"">
</span></span></span><!--[endif]-->How to discern between
fixed, generally accepted industry-wide procedures and the
deviations and more nuanced approaches as employed in a
particular hospital, in a particular ward, or only by a
particular doctor? How can such a layered approach help to
give feedback either to improve the model, or to improve a
ward’s or a doctor’s practices?<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Work on this PhD topic will be conducted as
part of the Hospital@Night project – a grand solution project
funded by the
<a href="https://innovationsfonden.dk/en"
moz-do-not-send="true">Innovationfund Denmark</a>. Within
this project, you will collaborate closely with machine
learning specialists from the
<a href="https://cs.au.dk/research/data-intensive-systems/"
moz-do-not-send="true">Data-Intensive Systems Group</a>,
healthcare IT experts from
<a href="https://systematic.com/healthcare/"
moz-do-not-send="true">Systematic</a>, and medical
specialists from
<a href="https://www.en.auh.dk/" moz-do-not-send="true">Aarhus
University Hospital</a> and <a
href="https://aalborguh.rn.dk/service/english"
moz-do-not-send="true">
Aalborg University Hospital</a>.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><b>Qualifications and specific competences:<o:p></o:p></b></p>
<p class="MsoNormal">To apply for the position, you must have a
relevant master’s degree and excellent computer programming
skills. Prior experience in at least one of the following
areas is of advantage: data visualization, data science,
computer graphics, human-computer interaction, or database
technologies. You are expected to bring or develop the
necessary soft skills for working in teams, as well as for
managing and communicating your research progress. The same
holds for the necessary hard skills in software development
and scientific writing.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><b>Place of Employment and Place of Work:<o:p></o:p></b></p>
<p class="MsoNormal">The place of employment is Aarhus
University, and the place of work is Department of Computer
Science, Åbogade 34, 8200 Aarhus N, Denmark. Computer Science
started at Aarhus University in 1968 as a part of the
Department of Mathematical Sciences. In 1998, computer science
became an independent department at <a
href="http://cs.au.dk/" moz-do-not-send="true">
Aarhus University</a>. Today, the department has 125
employees with a great mix of nationalities, and 600 BSc and
MSc students on the programs Computer Science and IT product
development.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">As a PhD student, you are a valuable part
of the department. All PhD students get a support group of
experienced advisors outside their own research group. The
main purpose of the support group is to give feedback on the
PhD work to help you reach your full potential as PhD student,
and to ensure that any obstacles that may arise are overcome
as smoothly as possible. Another important aspect is
socializing with your peers across the department. The
department host an annual retreat for PhD students and
Postdocs, and social events are continuously organized by the
Junior Club, which is run by PhD students.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">The department is strong in both
theoretical and experimental computer science. In recent
years, we have seen close cooperation between different
research groups – even those that traditionally are perceived
as being far from each other. As we emphasize
multidisciplinary attitudes to research, no firm dividing
lines are drawn between the various strands of subjects, and
there is a lively interaction between all research areas.
Problem-oriented and inter-disciplinary approaches
characterize our research.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><b>Applicants seeking further information
are invited to contact:<o:p></o:p></b></p>
<p class="MsoNormal">Assoc. Prof. Hans-Jörg Schulz<o:p></o:p></p>
<p class="MsoNormal">Department of Computer Science<o:p></o:p></p>
<p class="MsoNormal">Aarhus University<o:p></o:p></p>
<p class="MsoNormal"><span lang="DE">E-mail: <a class="moz-txt-link-abbreviated" href="mailto:hjschulz@cs.au.dk">hjschulz@cs.au.dk</a><o:p></o:p></span></p>
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