PhD in Complex Networks: Theory, Data & Modeling

Leiden University; Leiden; Hybride; EUR 36 000 - 45 000; Plein temps

Avantages offerts par ce poste

Hybrid work possible

Laptop provided

Public transport reimbursement

Pension ABP

30 leave days

Home-working allowance

Résumé du poste

Leiden University’s Mathematical Institute (MI) invites applications for a PhD Candidate in Complex Networks, co-supervised with LIACS. The position starts as soon as possible and no later than April 2027, with research spanning network science, spatial models, and data-driven analysis.

You will join the Leiden AlFa group and the Probability research group, contribute to a publication-based thesis, and collaborate with the Network Science group in a highly international environment.

Qualifications

• A university degree in mathematics, computer science or a closely related field.
• Knowledge in network science/complex networks (graph theory, probability, random graphs, topological data analysis).
• Programming experience, preferably in Python; willingness to develop computational skills.
• Strong motivation for academic research.
• Good English communication skills.
• Ability to work independently and in a team.
• You live or will relocate to the Netherlands by start date; master's degree by spring 2027 is acceptable.

Responsabilités

• Conducting complex networks research at the intersection of mathematics and computer science.
• Writing a publication-based PhD thesis.
• Engaging in a limited number of teaching and supervision activities.

Connaissances

Python programming

Network research

Academic motivation

English communication

Team and independent work

Formation

Math/CS degree

Description du poste

Leiden University’s Mathematical Institute (MI) invites applications for a PhD Candidate in Complex Networks, co-supervised with LIACS. The position starts as soon as possible and no later than April 2027, with research spanning network science, spatial models, and data-driven analysis.

You will join the Leiden AlFa group and the Probability research group, contribute to a publication-based thesis, and collaborate with the Network Science group in a highly international environment.