Responsibilities include teaching day and evening, undergraduate and graduate courses, in both disciplines—Statistics and Data Analytics—and conducting scholarly research, external funding and university service. The expected teaching load is three and four courses per year for non-tenured and tenured-faculty members, respectively
The successful candidate for the appointment at any level must have a PhD in Statistics or a closely-related area with expertise and interest in data analytics or big data related to artificial intelligence, machine learning, statistical learning, statistical computing or Bayesian methodology. ABD candidates will be considered if completion of all requirements for the Ph.D. degree will be completed prior to beginning employment
Title of Position Assistant/Associate/Full Professor-COB Management Science and Statistics Requisition Number TT20180009P Department Posting Name Management Science & Statistics Location Main Campus Recruitment Type External Position Type This is a Tenure Track Faculty, benefits eligible position Grant Funded? No Hours per week 40 If employee will be working a schedule other than Monday - Friday, 8:00am - 5:00pm, specify hours and days to be worked Flexible Schedule If Temporary, Ending Date Recruiting Rate The salary and supporting start-up package are competitive and commensurate with qualifications and experience. Beginning Salary Flexibility Yes Pay Basis Salary Required Education Doctoral Degree Do you want to allow additional experience to substitute for required education? No Preferred Education Field of Study An earned Doctoral Degree (Ph.D.) in Statistics or a closely related area. MS Office Experience Required Will this position require driving a UT or personally owned vehicle? No Other Computer and Software Skills Required Experience and Other Skills Required The successful candidate for the appointment at any level must have a PhD in Statistics or a closely-related area with expertise and interest in data analytics or big data related to artificial intelligence, machine learning, statistical learning, statistical computing or Bayesian methodology. ABD candidates will be considered if completion of all requirements for the Ph.D. degree will be completed prior to beginning employment. Candidates should support an area of application of interest to the department such as biology, business, cloud computing, computationally intensive methods, cyber security, engineering, statistical learning, machine learning or health. Applicants must have demonstrated (at the rank of Associate or Full) or potential (at the rank of Assistant) excellence in teaching, mentoring and advising of students, scholarly research and strong communication skills commensurate with an appointment at the specified rank. Do you want to allow additional education to substitute for required experience? No Other Skills Preferred The successful candidate must demonstrate interest or experience in working on applied data projects, an active (at the rank of Associate or Full) or potentially active (at the rank of Assistant) extramural funding program, external consulting with research centers or other quantitative institutes and a willingness to develop collaboration with other colleges and organizations. Candidates with research and funding interest in statistical learning, statistical computing and Bayesian methodology are preferred. Description of Job Duties Responsibilities include teaching day and evening, undergraduate and graduate courses, in both disciplines—Statistics and Data Analytics—and conducting scholarly research, external funding and university service. The expected teaching load is three and four courses per year for non-tenured and tenured-faculty members, respectively. This position is part of a university-wide cluster hiring initiative , this year in Artificial Intelligence, a part of President Taylor Eighmy’s ambitious vision for UTSA to become an urban-serving, multi-cultural discovery enterprise. UTSA’s research portfolio has increasingly becoming more transdisciplinary, cutting across areas such as cybersecurity, brain health, engineering, biomedicine, public health, educational transformation, sustainability, business and policy. These areas of research have been further fueled by focused faculty cluster hires in areas including cloud computing, cybersecurity, brain health and analytics and data science. This targeted faculty cluster hire in AI will build on and leverage our established research portfolio, propelling our ability to tackle and solve previously unsolvable problems. Hires are expected to build their own unique programs of research, as well as to collaborate with other hires in this cluster and with colleagues in their home department, college, and other colleges. Furthermore, San Antonio is a recognized cyber-analytics hub. Given the complexity of problems in transdisciplinary fields, and the opportunity for greater government and industry partnerships, UTSA has established The National Security Collaboration Center ( NSCC ), to support national security and global defense research in cybersecurity and cloud computing, cyber-attack/deterrence, critical infrastructure protection, analytics, high performance computing, AI, machine learning and visualization. These positions will facilitate outstanding collaborative research to further connect partners in the NSCC ecosystem. NSCC Background: https://www.utsa.edu/strategicplan/tactical-initiatives/nscc/index.html Posting Open Date 08/09/2018 Posting Close Date at midnight on Open Until Filled Yes Special Notes To Applicants -Associate or Full Professor applicants must also submit student evaluations of their teaching. Please attach in “Documents Needed to Apply” section of application - UTSA is a tobacco-free campus. - UTSA is an Equal Employment Opportunity/Affirmative Action Employer. Minorities, women, veterans, and individuals with disabilities are encouraged to apply. -This is a security sensitive position. Employment is contingent upon a successful background check. -Applicants who are selected for interviews must be able to show proof that they are eligible and qualified to work in the United States by time of hire. -At the discretion of the hiring department, this position posting may be closed once a sufficient number of qualified applications has been received.
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