Postdoctoral Research Positions – Control and Machine Learning (ERC CoDeFeL Project)
Institution: FAU DCN-AvH – Chair for Dynamics, Control, Machine Learning and Numerics
Location: Germany
Department: Mathematics
Application Deadline: 9 May 2025
Project: Control for Deep and Federated Learning (CoDeFeL)
Funding: Horizon Europe – ERC
Positions Available: 2 Postdoc positions
Project Overview:
The ERC-funded project CoDeFeL (Control for Deep and Federated Learning), led by Prof. Enrique Zuazua, explores cutting-edge interactions between control theory and machine learning. The successful candidates will join a dynamic interdisciplinary team addressing theoretical and computational challenges in data-driven modeling and distributed learning systems.
Key Research Topics:
Control theory for neural networks
Federated learning systems
Partial differential equations and numerics
Optimization in machine learning
Stability and robustness in distributed models
Eligibility Criteria:
A PhD in Mathematics, Applied Mathematics, Computational Sciences, or related fields
Proven research background in at least one of the following: control theory, machine learning, deep learning, numerical analysis, PDEs, optimization
Strong publication record
Good command of English (spoken and written)
Eligible Fields to Apply:
Mathematics
Applied Mathematics
Control Theory
Machine Learning
Computational Sciences
Optimization
Computer Science
Contract & Benefits:
Full-time position
Duration and salary to be defined based on qualifications and institutional framework
Access to the international FAU research network and mentoring under the ERC framework
How to Apply:
Apply online via:
For more information about the group and ongoing projects:
https://dcn.nat.fau.eu/
Contact: Prof. Enrique Zuazua – Chair for Dynamics, Control, Machine Learning and Numerics, FAU
Position Start Date: As soon as possible after selection.
