Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- University of Groningen
- University of Southern Denmark
- Austrian Academy of Sciences, The Human Resource Department
- Cranfield University
- DAAD
- Ghent University
- Inria, the French national research institute for the digital sciences
- Leiden University
- National Research Council Canada
- Nature Careers
- TU Dresden
- Technical University of Denmark
- VU Amsterdam
- 3 more »
- « less
-
Field
-
to an international team a strong background in one or more of the following areas: field programmable gate arrays (FPGAs), hardware description languages (e.g. VHDL or Verilog), high-level synthesis (HLS), artificial
-
++ programming languages and data analysis techniques General knowledge of microelectronics and FPGAs (VHDL or Verilog) is desirable Knowledge in radiation physics and dosimetry Interdisciplinary collaboration
-
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
-
++, etc.); experience with FPGA and ASIC design flow; A collaborative spirit for teamwork within diverse project groups; Excellent communication and presentation skills and creative thinking; Fluency in
-
, Computer Science, or related field with excellent grades. Sound knowledge of computer hardware design and synthesis tools (ASIC, FPGA). Good programming and scripting skills. Excellent English communication
-
design and synthesis tools (ASIC, FPGA). Good programming and scripting skills. Excellent English communication, presentation, and writing skills. Must be a team player. Knowledge of computing-in-memory is
-
synthesis tools (ASIC, FPGA). Good programming and scripting skills. Excellent English communication, presentation, and writing skills. Must be a team player. Knowledge of computing-in-memory is an added
-
design and synthesis tools (ASIC, FPGA). Good programming and scripting skills. Excellent English communication, presentation, and writing skills. Must be a team player. Knowledge of computing-in-memory is
-
energy-efficient CMOS blocks implementing SSM-based LLMs. Prototype hardware blocks on FPGA and prepare for ASIC tape-out. Benchmark performance and comparison with transformer accelerators. Work with
-
engineering a strong background in digital design, hardware description languages (e.g. Verilog, VHDL, SystemC), reconfigurable architectures (e.g. FPGA, CGRA) What we expect from you: above-average degree