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21 Aug 2025 Job Information Organisation/Company University of Cambridge Department Department of Engineering Research Field Neurosciences » Neuroinformatics Engineering » Control engineering
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 8 days ago
command of English, which is the working language of the department. German is an asset but not required. Our offer We are offering excellent working conditions in a highly interdisciplinary and stimulating
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Gregersen, Assoc. Prof. Luca Vannucci and Assoc. Prof. Battulga Munkhbat. We offer DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and
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interest in one (or two) research projects as part of your application: C01 – Synthesis of organic dyes and redox systems for controlled assembly in mol2Dmat heterostructures (Prof. Eigler, 2 positions
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available for a four-year term as part of the recently awarded ELSA Lab for Technical Industry (ELSA4TI) (funded within the NGF-Call AiNed ELSA Labs). The ELSA4TI Lab is led by Prof Ming Cao, Director of
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boundaries and abstraction levels is a must. Experience with control theory and spiking neural networks are a plus. Ability for collaborative work, interdisciplinary and cross-topical thinking. Very good
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at international conferences You will work here The research is embedded within the chair Experimental Zoology , led by Prof. Florian Muijres . You will be supervised by Dr. Antoine Cribellier .
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of Prof. Dr. Frank Cichos and Dr. Nico Scherf (Max Planck Institute for Human Cognition and Brain Sciences). The position is part of a collaborative project in the Center for Scalable Data Analytics and
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are encouraged to apply. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates
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, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from nonlinear control and optimisation