BYR Achieve · 镜像论坛

Boise State University招收Ph.D. Boise State University Neuromorphic Computing Group Graduate Student Opportunities Neuromorphic Systems Group at Boise State University has funding opportunities for doctoral students to conduct research on next-generation computing systems based on neural learning. The multidisciplinary research involves synergistic development of nanoscale memristive (synaptic) devices, mixed-signal circuits and novel neural learning architectures. This research program will lead to development of pathbreaking computing architectures which can mimic learning in a mammalian brain and revolutionalize the way we compute, communicate and perform signal processing. We seek talented and motivated graduate students in all the following areas: · Nanoscale memristive device design, fabrication and modeling · Mixed-Signal integrated circuit design · Neural learning and pattern recognition system architectures Descriptions of the projects planned and the skills necessary are listed below. If you are interested in one of these positions, please contact the designated person with: a current CV, sample thesis, journal or conference paper, unofficial transcript, GRE/TOEFL scores and a carefully worded description of what you bring to the project and why the project is of interest to you. PhD Candidate 1: Mixed-Signal IC Design Contact: VishalSaxena@BoiseState.edu Neuromorphic custom circuit design for reconfigurable digital computing using memristive devices all integrated on a chip. Interfacing with FPGAs for read-out and test. Mixed-signal circuit implementation of artificial neural networks (ANNs) using memristive devices, all integrated on a chip. Involves translation of neural learning algorithms into chip hardware design. Required skills include signal processing; analog and digital circuit design, the ability to develop proficiency in new fields, and expertise in technical writing. PhD Candidate 2: FPGA prototyping for neural training Contact: VishalSaxena@BoiseState.edu Utilize FPGA to implement training algorithms for synaptic arrays and neurons fabricated on a chip. Skill set required same as position #1 PhD Candidate 3: Machine and biometric learning algorithms for silicon neurons Contact: EBarneySmith@BoiseState.edu Develop silicon biometric learning algorithm based on Hodgkin-Huxley conductance based model of a neuronal membrane Develop machine learning algorithms for neuromorphic computing Develop learning algorithms that do not require external training Required skills include programming, machine learning, basic circuit analysis, the ability to develop proficiency in new fields, and expertise in technical writing. PhD Candidate 4: Neuromorphic hardware development Contact: VishalSaxena@BoiseState.edu Design of embedded systems using neural learning chips and FPGAs. Required skills include expertise with FPGA, Verilog, hardware design skills, the ability to develop proficiency in new fields, and expertise in technical writing. PhD Candidate 5: Device fabrication and test Contact: KrisCampbell@BoiseState.edu Design memristive synapse devices using novel materials Design materials to tune device properties Fabricate and test devices in back end of line (BEOL) processes Required skills include materials characterization experience, fabrication skills, and familiarity with device testing systems, the ability to develop proficiency in new fields, and expertise in technical writing. PhD Candidate 6: Mixed-Signal IC Design Contact: VishalSaxena@BoiseState.edu Tape-out chip designs for silicon neural network based on designs generated by student 3 Skill set required as described in student 1 Post Doctoral 7: Computer Architecture Contact: VishalSaxena @BoiseState.edu Develop digital VLSI architecture to incorporate memristive synapse devices into an integrated neuromorphic system chip. Develop FPGA architectures utilizing neuromorphic system chip Skills needed include digital architectures, RTL design, synthesis, verification and tape-out, the ability to develop proficiency in new fields, and expertise in technical writing. PhD Candidate 8: Device test and analysis Contact: KrisCampbell@BoiseState.edu Materials analysis and device testing of higher voltage memristive devices Skills and responsibilities similar to student 5 PhD Candidate 9: Device modeling Contact: KrisCampbell@BoiseState.edu Statistical characterization of device performance Spice modeling of memristive devices Collect electrical characterization data Utilize electrical characterization to develop device models of novel synaptic device materials and memristive devices Develop Spice models of circuits and incorporating synaptic devices in neuromorphic computing applications Required skills include statistical analysis of electrical characterization data sets; Spice modeling experience; device testing experience; wafer level testing experience, the ability to develop proficiency in new fields, and expertise in technical writing. More information on the graduate programs in ECE at Boise State University is available at the link: http://coen.boisestate.edu/ece/students/graduate/