Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Cranfield University
- University of Groningen
- University of Southern Denmark
- ; The University of Edinburgh
- Forschungszentrum Jülich
- Lulea University of Technology
- ;
- Technical University of Denmark
- Ghent University
- NTNU - Norwegian University of Science and Technology
- The University of Edinburgh
- University of Nottingham
- ; Loughborough University
- ; Swansea University
- ; The University of Manchester
- ; University of Oxford
- AALTO UNIVERSITY
- Abertay University
- DAAD
- Duke University
- Eindhoven University of Technology (TU/e)
- Fluxim AG
- Fraunhofer-Gesellschaft
- Leiden University
- Ludwig-Maximilians-Universität München •
- Nature Careers
- TU Dresden
- Tel Aviv University
- The University of Chicago
- The University of Manchester
- UNIVERSITY OF VIENNA
- University of Antwerp
- University of Glasgow
- University of Nebraska–Lincoln
- University of Twente
- University of Vienna
- Université Laval
- Vrije Universiteit Brussel
- Yeshiva University
- 29 more »
- « less
-
Field
-
Infrastructure? No Offer Description Work group: PGI-15 - Neuromorphic Software Eco System Area of research: Promotion Job description: Your Job: The conventional, manual co-design of algorithms and hardware is
-
Your Job: The conventional, manual co-design of algorithms and hardware is slow and inefficient. Our group develops methods and tools to automate the co-design process. The core of this project is
-
Apply now The Faculty of Science, Leiden Institute of Advanced Computer Science, is looking for a: PhD Candidate, Efficient LLM Algorithm, Hardware and System Design (1.0 FTE) Project description We
-
filled. This fully funded PhD explores AI-native and sensing-aware wireless systems where communications and sensing are co-designed end-to-end. You will unify modern machine learning, statistical signal
-
benchmarks for these architectures. This will also guide hardware design for such devices and tackle crucial challenges in networked systems and entanglement transmission. Candidate’s profile Knowledge
-
of algorithms and digital neuromorphic hardware is an additional avenue for enhancing the efficiency of the methods. In this context the research will explore digital, event-based implementations
-
infrastructure. For reduced (CapEx) costs, greater flexibility and faster evolution, mobile core/radio network functions today are largely realised in software over commodity computing hardware in private/public
-
algorithms for application parallelization, simulators and virtual platforms for application- and architecture exploration, hardware/software co-design and operating/runtime systems. Typical application
-
into the co-design of ultra-low-power AI hardware architectures tailored for edge computing applications. The research aims to develop neuromorphic processors, FPGA/ASIC-based AI accelerators, and intelligent
-
elements like Physical Unclonable Functions (PUFs) and True Random Number Generators (TRNGs) to secure hardware components. Embedded Trust Protocols: Design protocols that establish and maintain trust within