Sort by
Refine Your Search
-
Listed
-
Country
-
Field
-
of experience preferred, but fewer years may be considered if relevant. Proven skills in PCB design, FPGA development, and signal processing. Proactive, organized, and comfortable working in a multicultural
-
, signal generators (including microwave), spectrum analyzers, soldering stations, and CAD software Experience with microcontrollers, FPGA programming, and LabVIEW Excellent communication skills. Ability
-
of the digital ASIC-design flow is required: logic synthesis, timing analysis, power simulation, logic equivalence, DFT and/or P&R. Knowledge of FPGA-development is a plus. Knowledge of low-power designs is a plus
-
infrastructure (e.g., OpenStack, OpenShift). Knowledge of sensor electronics, FPGA development (e.g., VHDL), and sensor electronics prototyping. Excellent written and oral communication skills. Motivated self
-
. (preferred) or M.Sc. in Electrical Engineering, Telecommunications Engineering, or a closely related field. SDR Expertise: Strong hands-on experience with SDRs (USRP, RFSoC, or equivalent). FPGA programming
-
central to developing advanced safety control systems that protect people in complex, high-risk environments, while also leading software development projects that integrate PLCs, FPGAs, and EPICS into next
-
PLCs, FPGAs, and EPICS into next-generation accelerator systems. Your work will help shape the future of safety engineering at Berkeley Lab and beyond, with opportunities to collaborate across DOE labs
-
related to developing, securing, or using AI chips and workloads, from edge devices to data centers. Topics of interest include, but are not limited to, GPUs, FPGAs, custom accelerators, protecting model IP
-
Communications protocols OSI stack UDP/TCP/IP Familiarity with wireless specifications such as cellular(4G/5G)/Wi-Fi (802.11) FPGA development Microcontroller and Digital Signal Processor (DSP) development MATLAB
-
Neuromorphic and AI-Optimized Processors – Design AI-specific chip architectures, including neuromorphic and domain-specific accelerators (TPUs, NPUs, FPGAs), for low-power and real-time AI processing. AI-Driven