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Work Performed Postdoctoral position on the theory (algorithms) and applications (robotics, cyber-physical systems, or healthcare/medicine) of machine learning and AI with an emphasis on one or more of the following areas: (1) Development of distributed learning, AI, and optimization methods that rely exclusively on local state and action information; (2) Development of black-box (or derivative-free) learning and optimization methods for the control of systems that lack explicit mathematical models and are common in human preference optimization, simulation-based optimization, or adversarial training; and (3) Development of methods to enable autonomous systems learn from their experiences, transfer knowledge and acquired skills to other learning agents and, ultimately, reason and act effectively in unknown environments.

DEFINITION: The Postdoctoral Appointee holds a PhD or equivalent doctorate (e.g. ScD, MD, DVM). Candidates with non-US degrees may be required to provide proof of degree equivalency. 1. A candidate may also be appointed to a postdoctoral position if the candidate has completed all of the requirements for a degree but the degree has not been formally conferred: in this case, the candidate may present evidence of completion of the degree requirements, together with a statement documenting the date on which the degree is to be conferred. If the degree is not conferred by this projected date, the postdoctoral appointment may be terminated. 2. Note for international candidates: Generally, immigration classifications (e.g., H-1B, J-1, etc.) require that the requisite degree be conferred before a petition can be filed or a visa document issued to sponsor the individual. The term of the appointment is limited (see Section 5 of the Postdoc Policy for length of appointment). The appointment involves substantially full-time research or scholarship, and may include teaching responsibilities. The appointment is generally preparatory for a full time academic or research career. The appointment is not part of a clinical training program, unless research training under the supervision of a senior mentor is the primary purpose of the appointment. The Postdoctoral Appointee functions under the supervision of a mentor or a department at Duke University. The Postdoctoral Appointee is expected to publish the results of his or her research or scholarship during the period of the appointment.

EXPECTATION: The conscientious discharge of research or scholarship responsibilities, which may include teaching responsibilities for Postdoctoral Associates Conformance to standards of responsible conduct in research Compliance with good scholarly and research practice Maintenance of a laboratory notebook and/or other comparable records of research activity, which remains the property of Duke University upon termination Adherence to University standards regarding use of isotopes, chemicals, infectious agents, animals, human subjects, and the like Open and timely discussion with the mentor regarding all facets of the Postdoctoral Appointee's research activities. Postdoctoral Appointees are encouraged to consult the AAMC Compact Between Postdoctoral Appointees and Their Mentors for suggested guidelines for the Postdoctoral Appointee-mentor relationship Prompt disclosure to the mentor regarding the possession and desire to distribute materials, reagents, software, copyrightable and potentially patentable discoveries derived from the Postdoctoral Appointee's research. Collegial conduct towards members of the research group and others as described in the Duke University School of Medicine Honor Code of Professional Conduct and other relevant conduct policies pertaining to other schools at Duke University. Compliance with all applicable University and departmental policies and procedures.

Required Qualifications at this Level Education/Training: A doctoral degree in the subject areas of mechanical engineering, electrical engineering, or computer science is preferred. Experience: Experience in the theory of machine learning and AI is required. Experience in one or more application domains (robotics, cyber-physical systems, medicine) is preferred.

Skills: The candidate should be able to formulate computational research questions in machine learning and AI independently and in a targeted manner, up to the level of leading and completing scientific publications involving collaborations both within and outside a local research group.

The intent of this job description is to provide a representative and level of the types of duties and responsibilities that will be required of positions given this title and shall not be construed as a declaration of the total of the specific duties and responsibilities of any particular position. Employees may be directed to perform job-related tasks other than those specifically presented in this description.

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