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Postdoctoral Fellow (f/m/x) in Modeling & AI in Neuro-Cognitive Aging
DZNE - German Center for Neurodegenerative Diseases
Magdeburg
Presencial
EUR 55.000 - 65.000
Tempo integral
Ontem
Torna-te num dos primeiros candidatos

Resumo da oferta

A leading research center in Germany is seeking a Postdoctoral Fellow in Modeling & AI in Neuro-Cognitive Aging to contribute to cutting-edge research. This role includes developing and implementing advanced models for disease progression, utilizing techniques in AI and deep learning. Candidates should have a PhD in relevant fields and strong programming skills. The position offers mentorship, access to quality datasets, and participation in international conferences. Flexible hours and a supportive work environment are part of the package.

Serviços

30 days holiday
Subsidized job ticket
Family support services

Qualificações

  • Completed PhD or equivalent research experience in Machine Learning or related field.
  • Strong foundation in statististics and modeling.
  • Experience with machine learning or statistical frameworks.

Responsabilidades

  • Develop disease progression models using innovative techniques.
  • Apply regression methods to analyze disease trajectories.
  • Integrate Deep Learning with Bayesian methods.

Conhecimentos

Machine Learning expertise
Multivariate statistics
Python programming
Deep Learning frameworks
Bayesian inference
Interdisciplinary research interest
Fluency in English

Formação académica

PhD in relevant field

Ferramentas

PyTorch
TensorFlow
Stan
scikit-learn
Descrição da oferta de emprego
Postdoctoral Fellow (f/m/x) in Modeling & AI in Neuro-Cognitive Aging
4068/2026/1
  • Magdeburg
  • 2 years, extension possible
  • 28.02.2026
  • full-time

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Your role in cutting edge research

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.
Your profile in cutting edge research

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.
  • Health promotion

    Because we know that familie is important, we support you with our family service

    Work-life balance

    We reconcile work and private life with flexible working hours, 30 days' holiday (On top free on Christmas Eve and New Year's Eve) and subsidised job/ Germany ticket options

    Remuneration and conditions according to TVöD-Bund

    Including annual special payment, capital-forming benefits and VBL supplementary pension scheme

    Your application

    Excellence in research thrives on diverse perspectives and experiences. We stand for a respectful and open culture. We promote equal opportunities, remove barriers, and welcome applications from people across all dimensions of diversity. Applicants with disabilities will be given priority in the case of equal suitability.

    Please submit your application as a single PDF inlcuding

    • 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 gabriel.ziegler@dzne.de

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

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