PhD-teaching assistant at TU/e

Research / Academic

Are you eager to work on a topic that brings together advanced network visualization and large event sequences analysis? 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 now!

'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 challenge: 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 diverse 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 international 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 ( and Prof. Fernando Paulovich (

The visualization cluster ( 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 master's degree (or an equivalent university degree) in Mathematics or Computer Science.
  • Interest in the discipline of Visualization and Visual Analytics.
  • Genuine interest in teaching.
  • Experience in coding with Javascript/Python and frontend frameworks (React, Angular).
  • Knowledge of graph theory and layout algorithms is considered a plus.
  • Skills in GPU graphics and computing libraries are considered a plus.
  • Good communication and team-working skills.
  • You are creative, critical, analytical, motivated, and persistent.
  • Fluent in spoken and written English (knowledge of Dutch is not required).

Salary Benefits:

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:

  • Full-time employment for five years, with an intermediate evaluation (go/no-go) after nine months.
  • To develop your teaching skills,you will spend 10% of your employment on teaching tasks.
  • To gain the competencies and qualities needed to be successful in your PhD and become an independent scientific researcher, TU/e has developed the TU/e PhD Competence Profile.
    researcher, TU/e has developed the TU/e PhD Competence Profile.
  • Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. €2,770 max. €3,539).
  • A year-end bonus of 8.3% and annual vacation pay of 8%.
  • High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
  • An excellent technical infrastructure, on-campus children's day care and sports facilities.
  • An allowance for commuting, working from home and internet costs.
  • A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.
  • Family friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.
Work Hours:

38 hours per week


De Rondom 70