Postdoctoral Fellow (f/m/x) in Modeling & AI in Neuro-Cognitive Aging 4068/2026/1

Helmholtz Association of German Research Centres; Deutschland; Vor Ort; EUR 45.000 - 60.000; Vollzeit

Zusammenfassung

A leading scientific research center in Germany seeks a Postdoctoral Fellow to advance research on neurodegenerative diseases, combining artificial intelligence with cognitive neuroscience. The successful candidate will develop disease progression models, collaborate in interdisciplinary teams, and contribute to high-impact publications. Applicants should have a PhD in a related field and strong skills in machine learning and statistics. The role offers mentorship and opportunities for professional development, embedded within a robust international research network.

Leistungen

Access to state-of-the-art infrastructure

Dedicated funding for international conferences

Mentorship and career support

Qualifikationen

• Completed PhD in Machine Learning, Computational Neuroscience, or related field.
• Strong foundation in multivariate statistics and modeling.
• Experience with Python and common machine learning frameworks.

Aufgaben

• Develop and implement disease progression models.
• Integrate Deep Learning approaches with Bayesian inference.
• Collaborate within an interdisciplinary team.

Kenntnisse

Machine Learning

Multivariate statistics

Modeling

Interdisciplinary collaboration

Fluency in English

Ausbildung

PhD in a related field

Tools

Python

PyTorch

TensorFlow

scikit-learn

Jobbeschreibung

Area of research

Scientific / postdoctoral posts

Job description

DZNE is a world-leading, internationally oriented center for cutting edge research on neurodegenerative diseases. The Modeling and Neuroprognosis Group at the DZNE invites applications for a Postdoctoral Fellow position at the intersection of modeling, artificial intelligence, cognitive neuroscience, and medicine.

This role is designed as a career accelerator for researchers who aim to combine academic excellence with skills that are highly relevant both in leading academic environments and in the growing AI–Health–Tech sector. You will work with state-of-the-art infrastructure, including 7T MRI, connectomics, and high-performance computing, while being embedded in a strong international research network with close collaborations with institutions such as UCL, Oxford, and Max Planck Institutes. Close mentorship and structured career support, including guidance on independent funding applications (e.g. ERC, DFG, BMBF), are provided. Researchers have access to large-scale, high-quality datasets, the DZNE’s ten-site network, and the CRC 1436, within an active international research environment. Dedicated funding supports participation in international conferences.

In this position, you will contribute to advancing how individual differences in neuro-cognitive aging and dementia are modeled and understood. Your tasks include:

• Developing and implementing novel disease progression models, including latent multimodal dynamics and state-space approaches.
• Applying uncertainty-aware regression methods, using parametric and non-parametric techniques, to characterize disease trajectories and deviations from healthy aging.
• Integrating Deep Learning approaches with Bayesian inference and latent variable models.
• Analyzing high-dimensional, multimodal data such as MRI, FLAIR, cognitive assessments, and fluid biomarkers.
• Contributing to high-impact scientific publications and presenting findings at international conferences.
• Collaborating closely within an interdisciplinary team across neuroscience, psychology, medicine, and data science.
• Mentoring junior researchers and supporting a constructive, collegial team culture.

We welcome applications from researchers with diverse academic backgrounds and career paths.

• A completed PhD in Machine Learning, Computational Neuroscience, Quantitative Psychology, Physics, Applied Mathematics, or a closely related field, or equivalent research experience.
• A strong foundation in multivariate statistics and modeling, for example in regression, Bayesian inference, representation learning, or generative models.
• Experience with Python and common machine learning or statistical frameworks such as PyTorch, TensorFlow, Stan, scikit-learn, or comparable tools.
• An interest in interdisciplinary research and openness to working across disciplinary boundaries, including psychology and medicine.
• Fluency in written and spoken English
• Motivation to further develop an independent research profile, either with a long-term perspective in academia or in applied research and industry.

Please submit your application as a single PDF including

• A cover letter describing your motivation and how this position aligns with your career goals.
• A curriculum vitae, including a list of publications where applicable.
• Two academic references
• Copies of relevant academic transcripts or certificates.

In case of questions regarding the position, please contact [e-mail]

If you have questions on the recruiting process, our Recruiting Team waits for your call:

This research center is part of the Helmholtz Association of German Research Centers. With more than 42,000 employees and an annual budget of over € 5 billion, the Helmholtz Association is Germany's largest scientific organisation.