Assistant Professor in Statistical Methods
2 weeks ago
Position Overview:
The International Society for Bayesian Analysis is seeking a qualified candidate for a tenure-track assistant professor role focused on statistical methodologies. The successful applicant will engage in research that emphasizes statistical and computational techniques applicable to large-scale data.
Departmental Context:
This position is situated within a robust academic environment that offers graduate programs, including Master's and Doctoral degrees in statistics. The department is committed to excellence in both research and pedagogy, fostering a collaborative atmosphere for methodological and interdisciplinary inquiries.
Research Focus:
Applicants should possess research interests that align with scalable Bayesian approaches and statistical techniques for extensive or intricate datasets. Specific areas of interest may include high-dimensional data analysis, statistical machine learning, uncertainty quantification, and network data analysis.
Key Responsibilities:
- Develop and maintain an active research agenda in statistics.
- Mentor graduate students and contribute to their academic growth.
- Deliver instruction in both graduate and undergraduate statistics courses.
- Participate in departmental service activities, including committee involvement.
The typical teaching load for faculty engaged in research is 6 credit hours per semester, with a reduced load for new faculty during their initial years.
Qualifications:
Applicants must hold a PhD in statistics or a closely related field with a strong emphasis on statistical principles. A complete application should include a cover letter, curriculum vitae, a research statement detailing past experiences and future plans, a teaching philosophy statement, and three letters of recommendation.
Additionally, candidates are encouraged to submit a statement outlining their commitment to diversity and inclusion within their professional practice.
Institutional Commitment:
The International Society for Bayesian Analysis is dedicated to fostering a diverse and inclusive academic community. We actively seek candidates from various backgrounds, including women, individuals of color, persons with disabilities, and veterans.
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