[Jobinfo] Fwd: [Ieee_vis_open_positions] PhD Position in Visual Analytics at Aarhus University
Wed Aug 28 12:49:33 CEST 2019
-------- Forwarded Message --------
Subject: [Ieee_vis_open_positions] PhD Position in Visual Analytics at
Aarhus University
Date: Tue, 27 Aug 2019 10:28:57 +0000
From: Hans-Jörg Schulz via ieee_vis_open_positions
<ieee_vis_open_positions@listserv.uni-tuebingen.de>
Reply-To: Hans-Jörg Schulz <hjschulz@cs.au.dk>
To: ieee_vis_open_positions@listserv.uni-tuebingen.de
<ieee_vis_open_positions@listserv.uni-tuebingen.de>
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.
*Topic: Visualization of Knowledge Graphs for Validation, Modification,
and Optimization*
**
*Apply here:
http://phd.scitech.au.dk/for-applicants/apply-here/november-2019/visualization-of-knowledge-graphs-for-validation-modification-and-optimization/*
*Research area and project description:*
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.
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.
Research questions to pursue in this project are:
**
·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?
·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?
·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?
Work on this PhD topic will be conducted as part of the Hospital@Night
project – a grand solution project funded by the Innovationfund Denmark
<https://innovationsfonden.dk/en>. Within this project, you will
collaborate closely with machine learning specialists from the
Data-Intensive Systems Group
<https://cs.au.dk/research/data-intensive-systems/>, healthcare IT
experts from Systematic <https://systematic.com/healthcare/>, and
medical specialists from Aarhus University Hospital
<https://www.en.auh.dk/> and Aalborg University Hospital
<https://aalborguh.rn.dk/service/english>.
*Qualifications and specific competences:*
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.
*Place of Employment and Place of Work:*
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 Aarhus University <http://cs.au.dk/>. 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.
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.
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.
*Applicants seeking further information are invited to contact:*
Assoc. Prof. Hans-Jörg Schulz
Department of Computer Science
Aarhus University
E-mail: hjschulz@cs.au.dk
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