TU Delft

PhD Position Graph Neural Networks for Network Time Series

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PhD Position Graph Neural Networks for Network Time SeriesFaculteit/afdeling: Faculty Electrical Engineering, Mathematics and Computer Science
Niveau: Universitair
Functie-omvang: 32-38 uur per week
Contractduur: 5 years
Salaris: nader overeen te komen U bekijkt een vacaturetekst oorspronkelijk opgesteld in het Engels.
Delen kunnen beschikbaar zijn in het Nederlands! Faculty Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three disciplines - electrical engineering, mathematics and computer science. Combined, they reinforce each other and are the driving force behind the technology we use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make future-proof. We are also working on a world in which humans and computers reinforce each other. We are mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. There is plenty of room here for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1,100 employees and 4,000 students work and study in this innovative environment.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

The Department of Intelligent Systems conducts fundamental research, engineering and design in the interlocking fields of data processing, interpretation, visualization and interaction using model- and knowledge-based methods and algorithms. The research is inspired by challenges from the domains of consumer electronics and entertainment, cultural heritage, social media, medical and health sciences, security and privacy, and safety and incident management. The department underpins the EEMCS thematic research lines Data Science, Safety & Security, and Health & Wellbeing. EEMCS academic members involved in AidroLab are Prof. Alan Hanjalic from the Multimedia Computing group and Prof. Geert Leus from the Cirucit and Systems group.

Functie omschrijving

AidroLab is Delft Artificial Intelligence Lab (DAI-Lab) for urban water systems. As cities face growing pressure from climate change and increasing demographics, AidroLab’s mission is to develop AI solutions for sustainable water management and effective flood control. AidroLab will carry out cutting-edge fundamental and applied research in Geometric Deep Learning (GDL), exploiting digitisation to tackle water problems in the urban environment. Contrary to conventional AI techniques, GDL can effectively take the complex interrelationships of water networks and urban systems into account, allowing the development of ground-breaking data-driven solutions. The methods and tools developed by AidroLab will enhance the adaptability and resilience of urban water systems and help decision-makers and first responders to address known criticalities and uncertain future conditions.

AidroLab will employ 4 PhD students: two at the Faculty of Civil Engineering and Geosciences (CEG) and two at the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS). While CEG students will focus on the application of AI to solve real problems related to urban water systems, EEMCS students will carry out fundamental research in Graph Neural Networks to provide better modelling tools. AidroLab research will be based on a strong collaboration among all the employed PhDs and research groups involved.

The following positions is open for the PhD of EEMC Faculty:
PhD position “Research on Graph Neural Networks for Network Time Series”

The research will concern both the theoretical and practical study and exploration of network-data coupling for developing novel learning methods.

Department
AidroLab is a Delft Artificial Intelligence Lab (DAI-Lab). Artificial intelligence, data and digitalisation are becoming increasingly important when looking for answers to major scientific and societal challenges. In a DAI-lab, experts in ‘the fundamentals of AI technology’ along with experts in ‘AI challenges’ run a shared lab. As a PhD, you will work with at least two academic members of staff and three other PhD candidates. In total, TU Delft will establish 24 DAI-Labs where 48 Tenure Trackers and 96 PhD candidates will have the opportunity to push the boundaries of science by using AI. Each team is driven by research questions which arise from scientific and societal challenges and contribute to the development and execution of domain specific education. Instead of the usual 4-year contract, you will receive a 5-year contract. Approximately a fifth of your time will be allocated to developing ground breaking learning materials and educating students in these new subjects. The experience you will gain by teaching will be invaluable for future career prospects. All team members have many opportunities for self-development. You will be a member of the thriving DAI-Lab community that fosters cross-fertilization between talents with different expertise and disciplines.

The DAI-Lab AidroLab is led by Dr. Riccardo Taormina of the Department of Water Management (CEG) and Dr. Elvin Isufi of the Department of Intelligent Systems (EEMCS).

Functie eisen

  • MSc degree in computer science, electrical engineering, or applied sciences relevant to the Ph.D. topic;

  • Demonstrated competence in graph-based data processing including graph neural networks, graph signal processing, network data science, and multi-modal/relational deep learning.

  • Affinity with teaching and guiding students.

  • Drive to conduct theoretical and practical research in graph neural networks.

  • A proven record and interest in further developing modelling, programming, analytical and scientific writing skills.

  • Proficiency in verbal and written English and Python especially Pytorch/Tensorflow.

  • Team-work, self-initiative, and a deadline oriented profile.

Arbeidsvoorwaarden

TU Delft offers DAI-Lab PhD-candidates a 5-year contract (as opposed to the normal 4-years), with an official go/no go progress assessment after one year. Approximately a fifth of your time will be allocated to developing ground breaking learning materials and educating students in these new subjects.
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3217 in the fifth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills. The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.

Informeren en solliciteren

Questions about the vacancy and application portfolio should be sent Dr. Elvin Isufi at e.isufi-1@tudelft.nl.

To apply for these positions, please submit the following documents:


  • Motivation letter (2 pages at most)

  • Updated CV

  • (part of your) MSc thesis or a paper that you have written in which you demonstrate your writing skills.

Please highlight in your motivation letter and/or CV examples of projects and achievements that demonstrate your relevant competencies.

Please note that applications will be periodically reviewed also before the application deadline until a suitable candidate is found, therefore the position might be closed earlier. When applying for this position, please refer to vacancy number TUD00268. Please email your application to Anita Lacroix, email: vacancies-EEMCS@tudelft.nl.

A pre-employment screening can be part of the application procedure.

Acquisitie naar aanleiding van deze vacature wordt niet op prijs gesteld.

Uren per week: 32-38 uur per week

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