Assistant Professor - Machine Learning/Optimization (HDSI/ECE)
- Employer
- University of California San Diego
- Location
- California, United States
- Salary
- Salary Not specified
- Date posted
- Nov 22, 2022
View more
- Position Type
- Faculty Positions, Science, Technology & Mathematics, Computer Sciences & Technology, Engineering
- Employment Level
- Tenured/Tenured Track
- Employment Type
- Full Time
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The University of California, San Diego invites applications for a
tenure-track faculty position in Machine Learning Theory and
Systems with focus a in Optimization. This will be a joint
appointment in the Halicioglu Data Science Institute (HDSI) and
Department of Electrical and Computer Engineering (ECE). The
appointment will be at the Assistant Professor level (tenure
track). Salary is commensurate with qualifications and based on UC
salary scales.
Data science and machine learning methods have already transformed the design practices in ECE. Conversely, information and signal processing techniques at the core of ECE curriculum have become vital tools in modern day data science and machine learning.
The relentless growth of data in all aspects of society and technology will undoubtedly strengthen the symbiotic relationship between data science and electrical engineering to develop foundational optimization methods to process the data sets and data streams, leading to still-to-be-imagined data-driven algorithms, processes, and intelligence. At UCSD, HDSI is home to TILOS, an NSF AI Institute focused on foundations of optimization and engineering applications including computer-aided chip design, and wireless network optimization. The Department of Electrical and Computer Engineering has traditionally had a strong presence in statistical signal processing and information theory, serving the educational and research mission of HDSI. This joint faculty search seeks to leverage the success of these existing programs and continue to build a strong group in Machine Learning Theory and Systems with special emphasis in Optimization methods.
The successful appointee will be expected to teach graduate and undergraduate students at HDSI and ECE, with teaching load for each unit commensurate with the appointment. Candidates are expected to establish a vigorous program of high-quality research that focuses on innovations in Machine Learning Theory and Systems.
Basic qualifications (required at time of application)
PhD or Advancement to Candidacy in Data Science, Computer Science, Engineering, or related discipline.
Preferred qualifications
We seek applicants with an outstanding track record of research accomplishments, excellence in teaching, service, and a commitment to support diversity, equity and inclusion at the university.
Document requirements
o
Cover Letter
o
Curriculum Vitae - Your most recently updated C.V.
o
Statement of Research
o
Statement of Teaching
o
Teaching Evaluations (Optional)
o
Statement of Contributions to Diversity - Applicants should summarize their past or potential contributions to diversity. See our http://facultydiversity.ucsd.edu/recruitment/contributions-to-diversity.html site for more information.
o
Misc / Additional (Optional)
o
COVID-19 Impact Statement - We understand that the COVID-19 pandemic may have had a substantial impact on academic productivity. In our academic hiring processes, we will be keeping this in mind as we consider achievement relative to opportunity. We encourage you to reflect on constraints on opportunity in your field that were caused by the events of the pandemic and where applicable, to discuss your achievements in this light.
(Optional)
Additional information is available online at https://apptrkr.com/3638879.
Data science and machine learning methods have already transformed the design practices in ECE. Conversely, information and signal processing techniques at the core of ECE curriculum have become vital tools in modern day data science and machine learning.
The relentless growth of data in all aspects of society and technology will undoubtedly strengthen the symbiotic relationship between data science and electrical engineering to develop foundational optimization methods to process the data sets and data streams, leading to still-to-be-imagined data-driven algorithms, processes, and intelligence. At UCSD, HDSI is home to TILOS, an NSF AI Institute focused on foundations of optimization and engineering applications including computer-aided chip design, and wireless network optimization. The Department of Electrical and Computer Engineering has traditionally had a strong presence in statistical signal processing and information theory, serving the educational and research mission of HDSI. This joint faculty search seeks to leverage the success of these existing programs and continue to build a strong group in Machine Learning Theory and Systems with special emphasis in Optimization methods.
The successful appointee will be expected to teach graduate and undergraduate students at HDSI and ECE, with teaching load for each unit commensurate with the appointment. Candidates are expected to establish a vigorous program of high-quality research that focuses on innovations in Machine Learning Theory and Systems.
Basic qualifications (required at time of application)
PhD or Advancement to Candidacy in Data Science, Computer Science, Engineering, or related discipline.
Preferred qualifications
We seek applicants with an outstanding track record of research accomplishments, excellence in teaching, service, and a commitment to support diversity, equity and inclusion at the university.
Document requirements
o
Cover Letter
o
Curriculum Vitae - Your most recently updated C.V.
o
Statement of Research
o
Statement of Teaching
o
Teaching Evaluations (Optional)
o
Statement of Contributions to Diversity - Applicants should summarize their past or potential contributions to diversity. See our http://facultydiversity.ucsd.edu/recruitment/contributions-to-diversity.html site for more information.
o
Misc / Additional (Optional)
o
COVID-19 Impact Statement - We understand that the COVID-19 pandemic may have had a substantial impact on academic productivity. In our academic hiring processes, we will be keeping this in mind as we consider achievement relative to opportunity. We encourage you to reflect on constraints on opportunity in your field that were caused by the events of the pandemic and where applicable, to discuss your achievements in this light.
(Optional)
Additional information is available online at https://apptrkr.com/3638879.
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