Enrique Zuazua
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Postdoctoral Research Assistant in PDEs, Control, and Machine Learning at Friedrich-Alexander-Universität Erlangen-Nürnberg Friedrich-Alexander-Universität Erlangen-Nürnberg in Germany
Degree Level
Postdoc
Field of study
Computer Science
Funding
The position is fully funded by the state of Bavaria, Germany, with a competitive international annual gross salary following the German TV-L (A13/E13) scale. The contract is for two years initially, with the possibility of extension. Some teaching duties are included, but there are no administrative duties.
Deadline
Feb 11, 2026
Country
Germany
University
Friedrich-Alexander Universität Erlangen-Nürnberg

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About this position
The Chair for Dynamics, Control, Machine Learning, and Numerics – Alexander von Humboldt Professorship (FAU DCN-AvH) at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany, is seeking applications for a Postdoctoral Research Assistant position. The research group, led by Professor Enrique Zuazua, focuses on cutting-edge topics at the intersection of partial differential equations (PDEs), numerical analysis, control, and machine learning. The successful candidate will join an international and interdisciplinary environment, collaborating with the FAU MoD Research Center for Mathematics of Data.
The position is full-time, initially for two years with the possibility of extension, and is funded by the state of Bavaria. The salary is competitive, following the German TV-L (A13/E13) scale. The role is primarily research-oriented, with some teaching duties and no administrative responsibilities. Research topics include PDE-constrained optimization and control, data-driven modeling for dynamical systems and PDEs, learning-based numerical methods, operator learning, structure-preserving numerical schemes, inverse problems, uncertainty quantification, and connections between control, reinforcement learning, and scientific machine learning.
Applicants must have a PhD in Applied Mathematics, Machine Learning, or a closely related field, with strong expertise in control and/or machine learning, proven research experience in PDEs and numerical analysis, and solid computational skills (e.g., Python, MATLAB). Excellent English communication skills and the ability to work both independently and collaboratively are essential. The group values diversity, inclusivity, and equal opportunity, and supports dual career couples and family-friendly policies.
To apply, candidates should submit a single PDF file containing a cover letter (with a brief description of their PhD thesis and previous postdoctoral activities, if applicable, and expectations for the position), a CV with a list of publications, reference information for 2-3 professors, and a one-page research proposal aligned with the ERC CoDeFeL project. Applications should be sent via email to [email protected] with the subject 'FAU Assistant 2026'. The deadline for applications is February 11, 2026, and applications will be reviewed on a rolling basis. Shortlisted candidates will be invited for an interview.
For more information, visit the FAU DCN-AvH Careers page or the official call.
Funding details
The position is fully funded by the state of Bavaria, Germany, with a competitive international annual gross salary following the German TV-L (A13/E13) scale. The contract is for two years initially, with the possibility of extension. Some teaching duties are included, but there are no administrative duties.
What's required
Applicants must hold a PhD in Applied Mathematics, Machine Learning, or a closely related field. Strong expertise in control and/or machine learning, proven research experience in partial differential equations and numerical analysis, and solid computational skills (e.g., Python, MATLAB) are required. Candidates should have an excellent command of English (written and spoken) and the ability to work independently and collaboratively in an international and interdisciplinary environment. A strong research track record and motivation to work across areas are expected.
How to apply
Submit your application as a single PDF file via email to [email protected]. Include a cover letter, CV with publications, reference information for 2-3 professors, and a one-page research proposal. Use the subject 'FAU Assistant 2026' in your email. Applications are reviewed on a rolling basis.
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