PhD Position Probabilistic Inference in Complex Networks

Are you curious about complex systems and learning hidden patterns from them? Do you enjoy exploring mathematical models and working with network data? Join our team!

Job description

Complex systems are often modeled with networks, structures where the main units of information are pairs or groups of nodes connected by edges. As network data becomes increasingly available across scientific domains, there is a need for principled models to analyze this specific structured data. How can we perform inference tasks to learn hidden patterns, like community structure or hidden hierarchies? How can we incorporate domain knowledge to design interpretable models for their governing mechanisms? How can we make these model computationally efficient and capable of scaling to large dataset sizes?

Scientific challenges for this exciting PhD project include:

• develop principled probabilistic generative models for networks
• analyze real network data from different application domains
• design efficient algorithmic implementations of the theoretical models

You will be supervised by Dr. Caterina De Bacco from the Network Architecture and Services Group.

You’ll become part of a diverse, enthusiastic team of academic staff, PhD students, and postdocs in the Network Architectures and Services Group, part of the Quantum & Computer Engineering department. Together, we explore the characteristics of complex networks, from engineering infrastructures to biological, brain, and social systems. We foster a friendly, supportive environment where we regularly meet, exchange ideas, and collaborate. You’ll also receive comprehensive training to help you grow as a researcher.

Job requirements

In order to be successful, you will have:

• MSc in Physics, Mathematics, Engineering, Computer Science, Statistics or related disciplines with a strong background in mathematical modeling, algorithms and probabilistic modeling
• Good programming skills in Python/C/C++
• Good oral and very good written skills in English
• Enjoys working in an international and inter-disciplinary research group

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis.

TU Delft (Delft University of Technology)

At TU Delft, you will work in an international research environment focused on science, engineering and design, addressing challenges in energy, climate, mobility, health and digital society.

Faculty of Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines that reinforce each other in research and education. The faculty offers strong international positioning, innovative research opportunities, and excellent labs and facilities.

Conditions of employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months, followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

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 a monthly work costs contribution. Flexible work schedules can be arranged.

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible. The HR unit, Coming to Delft Service, offers information to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available to support your accompanying partner with their job search in the Netherlands.

As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. This is done, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest.