Asst/Assoc/Full Professor-Asst/Assoc/Full Scientist AI/ML
The University of Kansas

Lawrence, Kansas

Posted in Education and Training


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Job Info


Position Overview
The University of Kansas (KU) Department of Electrical Engineering and Computer Science (EECS) and the Institute for Information Sciences (I2S) seeks outstanding individuals for a joint tenure/tenure-track position at the rank of Asst/Assoc/Full Professor (tenure/tenure-track)/Assist/Assoc/Full Scientist in Electrical Engineering with a focus on Artificial Intelligence and Machine Learning. Successful candidates are expected to contribute to the development of academic programs and contribute to the research community. Applicants are expected to have an earned doctorate in Computer Science, Computer Engineering, Electrical Engineering or a closely related field at the time of appointment.

Applicants are expected to develop and sustain a research program focusing on foundational research of an interdisciplinary nature. Applicants focusing on machine learning and data mining are encouraged to apply. The expertise of interest includes, but is not limited to, artificial intelligence, big data analytics, design and optimization of deep learning and neural networks, software/hardware implementation of machine learning algorithms, data science, and their applications in science and engineering. Applicants pursuing research in areas that are synergistic with KU's recent Research Rising efforts on Securing Our Worlds: Physical, Digital, Social (https://research.ku.edu/news/kus-research-rising-awards-will-address-cri...) are preferred.

EECS is the largest department in the KU School of Engineering with 36 faculty members and a research volume of over $6 million per year. Faculty engage in research projects across multiple areas of interest through the department, the Institute for Information Sciences (I2S), the Center for Remote Sensing and Integrated Systems (CReSIS), and the KU Medical Center. The EECS department offers undergraduate and graduate degrees in electrical engineering, computer engineering, computer science, and interdisciplinary computing. The department has approximately 850 undergraduate and 200 graduate students. The KU School of Engineering has added new faculty lines over a five-year period and has expanded research and teaching facilities.

I2S is a University of Kansas designated research institute that advances knowledge and creates innovative technologies in cybersecurity, telecommunications, information systems, bioinformatics, and radar. I2S is one of the largest research institutes at the University of Kansas, with state-of-the-art facilities supporting various multidisciplinary inquiries. I2S-affiliated faculty members have served as federal program directors at NSF, DARPA, and NASA. The labs within I2S have computing resources, facilities for layout and construction of RF/radar systems, and programming expertise, which are supported by dedicated technical staff. I2S recently received support from the NSA to improve security for the Internet of Things, becoming one of only six universities selected to host an NSA lablet.


Job DescriptionPosition Overview continued:
The University of Kansas School of Engineering (SoE), the EECS Department, and I2S strongly value diversity, equity, inclusion, and belonging (DEIB). We seek candidates who can contribute to fostering an inclusive culture. In Spring 2019, KU SoE was one of only 29 universities to achieve the exemplar, inaugural ASEE Diversity Recognition Bronze Award https://diversityrecognition.asee.org/award-recipients/. At the University of Kansas, diversity, equity, inclusion, and belonging are an important part of our culture and university strategic plan. Applications from members of underrepresented groups are encouraged, noting the value that differences bring to our organization, students, staff, faculty, and community. The successful candidate must be eligible to work in the U.S. by the effective date of the appointment.

Job Description:

50% - Electrical Engineering and Computer Science (EECS) - Asst/Assoc/Full Professor (Tenure/Tenure-Track)

Teaching (20%)
Research (20%)
Service (10%)

50% - I2S - Asst/Assoc/Full Scientist
Research (40%)
Service (10%)

Combined Job duties for this position as follows:
60% Perform and conduct research in the research centers/laboratories associated with the department. Establish a strong research agenda in areas of expertise that overlaps, supports, or expands the current research in the department, leading to external grant support and publication in recognized refereed journals and conference proceedings. Collaborate with faculty and professional staff on KU campuses.

20% Teach undergraduate and graduate courses in the Electrical Engineering and Computer Science department. Participate in undergraduate and graduate student academic advising. Mentor graduate students in research and serve as the major advisor and chair of Master's and Doctoral level thesis committees.

20% Perform Department, School, University and professional service activities normally expected of university faculty commensurate with rank. Participating in local, national and international professional conferences and other activities appropriate to the discipline. Perform other duties as assigned by the Department Chair.
Required QualificationsFor the rank of Assistant Professor

  1. Earned doctorate in Computer Science, Computer Engineering, Electrical Engineering or a closely related field at the time of appointment.
  2. Expertise in artificial intelligence, big data analytics, design and optimization of deep learning and neural networks, software/hardware implementation of machine learning algorithms, data science, and their applications in science and engineering.
  3. Demonstrated potential for teaching Undergraduate/Graduate level courses at the University level.
  4. Potential to establish and secure external funding.
For the rank of Associate Professor
  1. Doctorate in Computer Science, Computer Engineering, Electrical Engineering or a closely related field at the time of appointment.
  2. Expertise in artificial intelligence, big data analytics, design and optimization of deep learning and neural networks, software/hardware implementation of machine learning algorithms, data science, and their applications in science and engineering.
  3. Proven record for teaching Undergraduate/Graduate level courses at the University level.
  4. Demonstrated ability to establish and secure external funding.

For the rank of Full Professor
  1. Doctorate in Computer Science, Computer Engineering, Electrical Engineering or a closely related field at the time of appointment.
  2. Expertise in artificial intelligence, big data analytics, design and optimization of deep learning and neural networks, software/hardware implementation of machine learning algorithms, data science, and their applications in science and engineering.
  3. Proven record for teaching Undergraduate/Graduate level courses at the University level.
  4. Strong record of established externally funded research.
Additional Candidate InstructionsA complete online application will include the following PDF files: 1) letter of application, 2) curriculum vitae, 3) a statement of research interests and plans, 4) a statement of teaching interests including plans for broadening participation in computing, 5) a diversity statement, typically on the order of two pages, outlining contributions and/or plans to contribute to diversity, equity, inclusion, and belonging (DEIB), and 6) contact information (including email addresses) for three individuals who can provide letters of recommendation.

In addition to the materials above, learning about each applicant's contribution and engagement in areas of diversity is an important part of KU's mission. As a result, applicants will be presented the following question at the time of application. The response must be within 4,000 characters or less.
  • Describe your experiences working with people from diverse backgrounds, and explain how those experiences reflect your commitments to diversity, equity, inclusion, and belonging?
Review of application materials begins November 2, 2022 and continues as long as needed to identify a qualified pool of candidates. Contact Information to ApplicantsErik Perrins
eecs_search@ku.edu Advertised Salary RangeCommensurate with experience and rank Application Review Begins02-Nov-2022 Anticipated Start Date18-Aug-2023


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