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National Laboratory of Pattern Recognition

Director Position Open


The National Laboratory of Pattern Recognition (NLPR), affiliated with the Chinese Academy of Sciences’ Institute of Automation (CASIA), Beijing, China, is looking for a full-time researcher serving as director for five-year term (2013-2017, extendible for a second term or as a researcher). The director is expected to lead the laboratory toward research soundness and visibility, through making development strategy, organizing research teams and activities.

The NLPR was founded in 1987 to become one of the first state key laboratories in China. Its research fields include the fundamentals of pattern recognition, image processing and computer vision, speech and language processing, and various applications. More information can be found at www.nlpr.ia.ac.cn/


PhD in pattern recognition or related fields

Well established and renowned in the international community

Experience of conducting key research projects and skills of team management

Professional dedication, willing to work at the laboratory in full time

Application Materials

CV including education and experience, research achievements, publications in the past 10 years

Thoughts of laboratory development and management

Copies of certificates of degree, awards and other support documents if any

Contact addresses of three referees

Important Dates

Application Submission:  by August 31, 2012

Interview and Notification: by September 30, 2012

Taking position: no later than December 31, 2012


Human Resource Department, Institute of Automation of CAS

95 Zhongguan East Road, Beijing 100190, China

Tel: +86-10-82614480

Email: hr@ia.ac.cn


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.

More information on the graduate programs in ECE at Boise State University is available at the link:


Open Position for a Chair Professor in Signal (and Image) Processing - Sweden


Luleĺ University of Technology is in an expansionary phase and is strengthening the information and communications technology field. One part of this effort is the recruitment of a professor in the research field of signal processing, with the task to lead the research subject and build a strong team.

Current research in signal processing is focused on measurement techniques, image analysis and telecommunications.

Deadline for application:

September 30 2012, ref. nr 1492-12


Jonas Ekman, Head of department    

Tel:  +46 920-49 28 28      

Email:  jonas.ekman@ltu.se

More information here.     




If you have any questions about living and working in Luleĺ and emigrating to Sweden please feel free to contact Matthew Thurley (matthew.thurley@ltu.se) who leads the industrial image analysis group within signal processing. 

Matthew grew up in Australia and moved to Luleĺ six years ago with his young family. "I have found excellent opportunities to build research projects, enjoy a relaxed lifestyle close to nature, and be part of a very family friendly society with excellent opportunities for my children."