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neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning rules in networks of complex spiking neuron models in the application field of geolocalization: Building
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, and training methods - across multiple technological platforms - photonics, electronics, biological neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning
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devices Develop hardware-aware machine learning models incorporating electronic and optical device constraints Design and implement hardware-efficient training methodologies for machine learning systems
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acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical devices Develop hardware-aware machine learning models incorporating electronic and optical
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SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf file to kerstin.achtruth at tu-dresden.de or to: TU Dresden, Chair of Algorithms, Prof. Dr. László Kozma, Helmholtzstr. 10
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a project linked to the “Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE)”. Your Job: Develop physics-aware simulations of growing cell populations, including their spatiotemporal
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Your Job: Join our team as a dedicated scientist and contribute to our exciting research projects. Our work focuses on models and algorithms for supervised and unsupervised learning. We devise deep
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for a researcher as of the Feb. 1st, 2026 (PhD position) as part of the reserach project BANNER. Your tasks: Develop AI algorithms for real-time fault detection, fault classification, and failure-mode
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the 01.02.2026 at the following conditions (PhD position): 50% = 19,92 hours Pay grade 13 TV-L limited 30.11.2028 Your tasks: Develop AI algorithms for real-time fault detection, fault classification
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support and training in classical and quantum modeling, quantum algorithms and computation, and battery materials and technology Further development of your personal and interdisciplinary strengths through