Description
As an Assistant Professor, responsibilities include teaching, research, and service in the Department of Electrical Engineering and Computer Science at the University of Arkansas, Fayetteville. This position is a 100% appointed, 9-month, tenure-track position.
Specifically, this position will conduct research leading to scholarly publications in the appropriate area, write proposals to obtain external funding, establish an independent and externally funded research program, develop graduate and undergraduate courses, provide curriculum material, construct syllabi, provide classroom instruction, write and administer exams, prepare and evaluate students, mentor students, serve on various faculty and student-oriented committees, exhibit participation and leadership in related professional societies and participate in the faculty decision-making for the Department of Electrical Engineering and Computer Science.
For this position, the Department of Electrical Engineering and Computer Science is seeking candidates whose research lies broadly in AI for Science. Areas of interest include, but are not limited to, the use of AI to generate hypotheses, design experiments, collect and interpret large datasets, and extract insights from complex data in disciplines such as physics, biology, chemistry, climate science, and materials science.
Regular, reliable, and non-disruptive attendance is an essential job duty, as is the ability to create and maintain collegial, harmonious working relationships with others.
For more information and to apply for this position: Applications should be submitted via the University of Arkansas Career Site:
https://uasys.wd5.myworkdayjobs.com/UAF_External_Career_Site/job/Fayetteville/Assistant-Professor---Engineering_R0073255-2
Requirements
Minimum Qualifications
- Ph.D. in computer science, computer engineering, electrical engineering, or closely related discipline from an accredited institution of higher education, conferred by the start of employment.
- Must present a promising track record in scholarship through refereed publications in conferences and/or journals.
- Experience in teaching and mentoring undergraduate and graduate students.
Preferred Qualifications
- Research expertise in the broad area of AI for Science, including, but not limited to, deep representation learning, generative AI, geometric deep learning, language modeling, physics-informed AI, AI-aided data collection, AI-based generation of scientific hypotheses, AI-driven experimentation and simulation, etc.
- Teaching experience in the field of computer science, computer engineering, or electrical in an accredited higher education environment.
- Exposure and/or experience writing grant proposals
