PhD Position - Multi-Scale Comparisons of Patterns of Concerted Activity and Causality in Cortical Neural Activity

Shape the future of data-driven neuroscience. Join the Helmholtz School for Data Science in Life, Earth and Energy () as a PhD candidate and work on an ambitious interdisciplinary project at the interface of data science, computational neuroscience and causal AI. You will collaborate with internationally recognized researchers and contribute to developing novel methods for understanding brain dynamics. The current opening for a PhD position is anchored at the Institute for Advanced Simulation - Computational and Systems Neuroscience () of Forschungszentrum Jülich, which consists of seven working groups that conduct research in the field of computational and systems neuroscience. The Statistical Neuroscience group headed by Prof. Sonja Grün develops computational methods to analyze the joint activity of neuronal networks, and applies these methods to experimental data in the context of international collaborations. Dr. Michael Denker, team leader at IAS-6, studies the relationship between the microscopic activity of individual neurons and mesoscopic population signals. His team develops open software for analysis and data management that forms the technical basis of the proposed project. The PhD candidate will be co-supervised by Prof. Adèle Helena Ribeiro, head of the Institute for Causal and Explainable AI in Life Sciences, RWTH Aachen University. Her group develops state-of-the-art methods in causal discovery and inference, with an emphasis on robustness, scalability, uncertainty quantification, expert knowledge integration, and multi-scale causal abstraction and representation learning.

Your Job

How are microscopic neuronal interactions linked to large-scale brain activity? In this PhD project, you will investigate how functional connectivity derived from neuronal spike activity relates to mesoscopic cortical dynamics, including oscillations and spatiotemporal activity patterns. By developing and applying advanced causal discovery methods for complex time-series data, you will establish a multi-scale framework to distinguish genuine neuronal interactions from confounding influences and uncover how precise neuronal coordination relates to large-scale brain dynamics.

To this end, the PhD candidate will

analyze state-of-the-art multi-scale electrophysiological data using modern analysis techniques
construct data-informed stochastic and deterministic simulations of activity data to model observed dynamics and to assess scientific hypotheses numerically
further develop the theoretical framework of the project
extend and develop methods to apply functional connectivity methods and causal frameworks to neuronal spiking data and link these to mesoscale activity representations
collaborate on project-related scientific software development and data management processes for reproducible science
contribute to the HDS-LEE graduate program through active engagement

Your Profile

A Master's degree with a strong academic background in physics, mathematics, computer science, or a related field
Proficiency in at least one programming language (Python, C++, …)
Experience in neuroscience is an advantage
Good analytical skills with a sound understanding of data evaluation
Good organisational skills and ability to work systematically, independently and collaboratively
Effective communication skills and an interest in contributing to a highly international and interdisciplinary team
Motivation for academic development, supported by bachelor’s and master’s transcripts and two reference letters
Working proficiency in English for daily communication and professional contexts (at least B2 level according to the , ideally supported by a certificate confirming the language level); Knowledge of German is beneficial

Our Benefits for You

We work on the very latest issues that impact our society and offer you the chance to actively help in shaping the change. This HDS-LEE PhD position will be located at Forschungszentrum Jülich with strong links to RWTH Aachen University. We offer ideal conditions for you to complete your doctoral degree:

World-class science environment at the interface between neuroscience and digital technologies, enabling scientific progress on the most complex known systems
Outstanding scientific and technical infrastructure
A highly motivated group as well as an international and interdisciplinary working environment at one of Europe’s largest research establishments
Continuous scientific mentoring by your scientific advisors
Chance of participating in (international) conferences
Unique (including data science courses, soft skill courses and annual retreats)
Depending on your qualifications and assigned responsibilities, you will be classified according to pay group 13 (75%) of the TVöD-Bund. In addition to the basic salary, there is an additional year-end bonus under the collective pay agreement amounting to 75% of a monthly salary, as well as capital-forming benefits. All information about the TVöD-Bund collective agreement can be found on the (pay scale table on page 66 ff. of the PDF download)
The position is for a fixed term of 3+1 years
Our International Advisory Service makes it easier for international employees to get started

We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender, disability, sexual orientation / identity, and social, ethnic and religious origin. A diverse and inclusive working environment with equal opportunities in which everyone can realize their potential is important to us.

The following links provide further information on diversity and equal opportunities: and on specific support options for women:

Place of Employment: Jülich

**Start Date:**To the next possible date

Salary: Pay Group 13 (75%) TVöD-Bund

Application Deadline: The position will be published until it is successfully filled.

Index Number: 2026D-0646