PHD-TEACHING ASSISTANT OPENING AT TU/E Network Visualization for Large Event-sequence Analysis
Position PhD-student
Irène Curie Fellowship No
Department(s) Mathematics and Computer Science
FTE 1,0
Date off 05/07/2024
Reference number V32.7509
Are you eager to work on a topic that brings together advanced network visualization and large event sequences anal- ysis? Contribute to a growing and challenging research field in a five year fully funded PhD-TA journey, investigating complex, multifaceted phenomena as well as industry processes. Then please apply!
“Traditional” visualization of time-changing (or dynamic) networks entails discretizing the time dimension, effectively “slicing” it into equally spaced intervals (e.g., daily, monthly, yearly). Real-life event sequences (e.g., tweets, Whatsapp calls, industry processes, physical contacts), however, present timestamps that do not match any obvious overlaying time structure: therefore, choosing a time resolution to “timeslice” such data is complex and prone to loss of precision. Aggregating events in the same timeslice means losing the exact order of events within it – this, in some contexts like contact tracing, is crucial information. Switching to a continuous time axis presents a two-fold chal- lenge: algorithms (and network layout techniques in particular) need to tackle this further complexity, possibly being more computationally expensive; plus very few approaches exist for visualizing, exploring, and, ultimately, analyze temporal networks in continuous time. On the other hand, a continuous time axis leaves the full temporal information available to the user, allowing for unlimited manipulation (like a image vector file over a raster image).
In this project, we aim at investigating novel visualization techniques for large event-based graphs, bridging the gap with the research topic of event sequence analysis, offering you the opportunity of building a robust expertise in di- verse research topics. As a PhD, you will obtain a profound knowledge of the theory and algorithms operating on event-based networks and apply it to cutting-edge visualizations and visual analytics tools. Confront and work with process mining experts to build prototypes that address real-world needs, following a rigorous yet creative research methodology. Collaborate closely with renowned experts from all Europe, working your way to impactful research both in industry and academia.
Benefit from a stimulating interdisciplinary environment, combining expertise in Data Science, Data Visualization, Process Mining. As part of our team, you'll receive comprehensive support and mentorship to develop your skills and expertise.
It is expected that the candidate will author high-quality scientific papers and showcase outputs of this work at inter- national conferences – and given the “Teaching Assistant” nature of this position, it is expected to actively contribute to the teaching activities of the group.
The project will be developed within the visualization cluster under the supervision of Dr. Alessio Arleo (a.arleo@tue.nl) and Prof. Fernando Paulovich (f.paulovich@tue.nl).
The visualization cluster (https://research.tue.nl/en/organisations/visualization) at TU/e has a strong track record in visualization and visual analytics for large event sequences and high-dimensional data. It has generated several award winning contributions at major visualization conferences (IEEE VIS, IEEE InfoVis, IEEE VAST, EuroVis); several successful start-up companies (MagnaView, Process Gold and SynerScope); and a number of techniques that are used on a large scale world-wide.
A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:
About us
Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.
Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video.
Information
Do you recognize yourself in this profile and would you like to know more?
Please contact Alessio Arleo, email a.arleo@tue.nl.
Visit our website for more information about the application process or the conditions of employment. You can also contact HR Services, email HRService.MCS@tue.nl.
Are you inspired and would like to know more about working at TU/e? Please visit our career page.
Application
We invite you to submit a complete application by using the apply button.
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We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.
We are an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude.
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