Postdoctoral Associate, Adam's Lab

We are looking for a highly motivated researcher to work on memristive-based neuromorphic circuits. The Adaptive Devices and Microsystems lab at the George Washington University conducts research in novel types of devices, circuits and hardware foundations for the next generation computing systems. Our research is currently focused on two-terminal non-volatile memory devices called memristors. These devices have shown an electrical behavior similar to that of artificial synapses and promise easy integration in efficient neuro-inspired processors.

The postdoctoral researcher will work in a multi-disciplinary environment, at the intersection between neuromorphic circuits and emerging devices. Relevant skills include mixed signal circuit design, device modeling, prototyping, programming, etc. The postdoctoral associate will participate in circuit design and device modeling efforts, planning and execution of the electrical measurements and prototypes, will analyze and interpret the data, contribute to funding reports and new proposal submissions, participate in mentoring students, will publish results, and will present the findings at conferences. The candidate will be mentored by Dr. Adam and supported by an inclusive research environment, and professional development goals will be discussed and fostered throughout the postdoctoral period. The researcher will participate in tape-outs together with the PI and PhD students in the Adam's group and benefit from our collaborations with U.S. national institutes and other academic partners.

Has, or will have by start date of the position, a Doctorate degree in Electrical and Computer Engineering or related.

Applicants must have fulfilled all requirements for the award of a PhD or equivalent qualification in a relevant field by the date of employment.

* Relevant research/work experience and demonstrated competencies in analog / mixed-signal circuit design;

* Strong skills in utilizing electrical characterization equipment are needed;

* Strong skills in relevant technical software, such as Cadence, SPICE, Verilog, etc. are needed;

* Background knowledge in neural network algorithms preferred, but not required

* Collaborative skills, student mentorship skills, result oriented approach, initiative, organization, and capacity to work in an interdisciplinary environment;

* Demonstrated ability to generate new ideas, concepts, models and solutions;

* Track record of research dissemination including peer-reviewed publications;

* Excellent communication skills (oral, written, presentation).

* Proficient written and spoken English is mandatory.

Will be tailored based on the specific profile of the candidate at the time of the interview.

Please provide three relevant publications (Journal and/or conference proceedings)

The university is an Equal Employment Opportunity employer that does not unlawfully discriminate in any of its programs or activities on the basis of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or expression, or on any other basis prohibited by applicable law.