Three PhD positions in visualization and visual analytics (1.0 FTE)

Three PhD positions in visual quality metrics, network visualization, and visualization for decision making.
JOB DESCRIPTION
We are looking for three bright PhD candidates to work in the area of visualization and visual analytics on the following topics:

Visual Quality Metrics (VQM) supervised by Dr Michael Behrisch
The aim of this project is to create next-generation Visual Quality Metrics and embed them into knowledge generation processes. VQMs are innovative visual feature and pattern descriptors that mimic the human’s powerful cognition and perception system; they (partially) automate the cognitively demanding task of finding interpretable visualizations. Embedded into Visual Analytics (VA) systems, VQMs will guide to primary domain/task specific visual patterns, while monitoring the progress for convergence and cognitive biases. This multidisciplinary project unites computer sciences with cognitive science insights. It builds on previous research, which demonstrates that guided visual pattern exploration raises trust and confidence in complex analytical scenarios. The novel VQM-enabled VA systems will have a far-reaching impact across sciences—from medicine to engineering, biology to physics—where Researchers are increasingly making use of big data. VQM-enabled VA will allow these domain experts to access complex datasets without data science expertise. This project will lay the foundation for a visual pattern-focused analysis, which in turn will be the key enabler for the user-centric, multi-faceted, and objective data exploration of the future.

Project-specific requirements (basic knowledge in one or more of the following areas will be considered an advantage): web-technologies and scalable data analysis platforms, visual data analytics, data visualization, machine learning, and AI. For detailed questions on this topic and the PhD itself feel free to contact m.behrisch@uu.nl.

Data Visualization for Decision Making (DEC) supervised by Dr Evanthia Dimara
There are decisions neither humans nor computers can make alone. Information Visualization leverages the human vision system -- the single most powerful system in our brain-- to support reasoning over complex information. The goal of this PhD project is to investigate how visualization systems can better support decision making with data in use cases where pure AI solutions appear inadequate, while the human intuition alone leads to biased judgments. While visualization research originates in computer science, this project opts to incorporate methodologies from other disciplines that study decisions, such as economics, psychology, cognitive, or management science. Visualisation solutions will further build on findings derived from empirical research, extracting user behaviour, expectations, and needs via both quantitative and qualitative approaches. Such findings are essential to ensure that the visual analytic systems do benefit the decision-makers and ultimately gain insights on how to refine them.

Project-specific requirements: Skills in any of the following: programming (preferably with web-technologies), data visualisation, experiment design, statistical analysis, machine learning, as well as multidisciplinary backgrounds would be desired. Independent thinking, curiosity, and enthusiasm will be celebrated. You are advised to visit evanthiadimara.com/work-with-me and contact Evanthia before applying.

Algorithms for Network Visualization (ANV) supervised by Dr Tamara Mchedlidze
One of the most common and intuitive network visualizations are so-called node-link diagrams. In these diagrams, nodes are depicted by geometric shapes such as circles or rectangles and links are represented by lines or curves connecting corresponding nodes. Algorithms for the construction of node-link diagrams are based on quality metrics, which are heuristic measures that specify how readable and appealing a visualization is. The goal of this project is to advance the state-of-the-art in network visualization algorithms. In particular, the goal of the PhD thesis is twofold. On the one hand, the aim is to develop network quality metrics that closely match the human perception of aesthetics, readability, and clarity of node-link diagrams. On the other hand, the goal is to develop algorithms that construct node-link diagrams by optimizing the newly developed quality metrics.

Project-specific requirements (basic knowledge in one or more of the following areas will be considered an advantage): design and analysis of algorithms, combinatorial optimization, machine learning, experimental evaluation of algorithms, empirical evaluation of visualization methods, graph theory, computational geometry, network information theory. For further information on the project and the requirements, you are highly encouraged to contact Tamara at t.mtsentlintze@uu.nl before applying.

As a PhD candidate in these fully funded 5-year projects, you will primarily perform research and publish your results in scientific papers in international conferences and journals, and complete a PhD thesis. You will also contribute to teaching by supervising tutorial groups and student projects and by co-teaching courses at the Bachelor's and Master's level (30% of employment time). This may lead to a University Teaching Qualification certificate.
REQUIREMENTS
We are looking for candidates with:

a Master’s degree in computer science, social sciences, design or relevant fields;
strong written and oral communication skills in English;
programming skills;
a strong motivation for conducting multidisciplinary research.
CONDITIONS OF EMPLOYMENT
a position for five years;
a full-time gross salary that starts at €2,395 and increases to €3,061 per month in the fourth year (scale P of the Collective Labour Agreement Dutch Universities (cao));
benefits including 8% holiday bonus and 8.3% end-of-year bonus;
a pension scheme, partially paid parental leave, and flexible employment conditions based on the Collective Labour Agreement Dutch Universities.

In addition to the employment conditions laid down in the cao for Dutch Universities, Utrecht University has a number of its own arrangements. For example, there are agreements on professional development, leave arrangements, and sports. We also give you the opportunity to expand your terms of employment yourself via the Employment Conditions Selection Model. This is how we like to encourage you to continue to grow.

More information about working at the Faculty of Science can be found here.

EMPLOYER
The three positions correspond to three distinct projects offered by Dr Michael Behrisch (VQM), Dr Evanthia Dimara (DEC) and Dr Tamara Mchedlidze (ANV) respectively. All PhD theses will be supervised jointly by each Assistant Professor (daily supervisor) and Prof Alexandru Telea (thesis promotor). You will also be part of the Visualization and Graphics (VIG) group. Main research areas of the VIG group are information visualization, human-computer interaction, graph, and network visualization, high-dimensional data visualization, visual analytics, and decision-making support.

We also provide the opportunity to have broad collaborations with other groups in our department (including Algorithms, Intelligent Software Systems, and Interaction divisions), as well as to conduct multidisciplinary research with scientists in Humanities, Social and Behavioural Sciences, Health Sciences, and Geosciences.

At the Faculty of Science, there are six departments to make a fundamental connection with: Biology, Chemistry, Information and Computing Sciences, Mathematics, Pharmaceutical Sciences and Physics. Each of these is made up of distinct institutes that work together to focus on answering some of humanity’s most pressing problems. More fundamental still are the individual research groups – the building blocks of our ambitious scientific projects.

Utrecht University is a friendly and ambitious university at the heart of an ancient city. We love to welcome new scientists to our city – a thriving cultural hub that is consistently rated as one of the world’s happiest cities. We are renowned for our innovative interdisciplinary research and our emphasis on inspirational research and excellent education. We are equally well-known for our familiar atmosphere and the can-do attitude of our people. This fundamental connection attracts Researchers, Professors and PhD candidates from all over the globe, making both the university and the Faculty of Science a vibrant international and wonderfully diverse community.

ADDITIONAL INFORMATION
If you have any questions regarding these positions, please contact Dr Michael Behrisch (m.behrisch@uu.nl), Dr Tamara Mchedlidze (m.mtsentlintze@uu.nl), or Dr Evanthia Dimara (e.dimara@uu.nl).

If you have a question about the application procedure, please send an email to science.recruitment@uu.nl.


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Utrecht University

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2021-03-29


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