Position ID: | YaleNUS-Science Division-TTT_DS [#18826] |
Position Title: | Open rank tenured or tenure track positions in Data Science |
Position Type: | Tenured/Tenure-track faculty |
Position Location: | Singapore, Lower Kent Ridge 138527, Singapore [map] |
Subject Areas: | Data Science / Machine Learning, Bayesian Statistics, Computational Statistics, High dimensional Data |
Appl Deadline: | finished (2021/06/20, finished 2021/08/30) |
Position Description: |
Yale-NUS College is a highly
selective liberal arts and science college in Singapore. Co-founded by Yale University and the
National University of Singapore, the College is committed to excellence in
research and teaching within a full residential programme that integrates living
and learning. Its curriculum educates
students in Asian and Western intellectual traditions as well as current
scientific thought. A student body of
1000 undergraduates from over 70 countries engages with more than 100
outstanding faculty from around the world through small classes and hands-on
research. Students and faculty also have access to the wider resources of two
world-leading research universities. The College invites applications for 2 open
rank tenure-track or tenured positions in Data Science. Preferred fields of
specialization are Bayesian Statistics, Computational Statistics, High
Dimensional Data and Machine Learning.
However, applicants working in other areas are welcome to apply. Applicants should have a relevant PhD and demonstrate an outstanding track record for their career stage. Research achievements should include publications in leading peer-reviewed journals or conferences commensurate with career stage as well as a demonstrated potential to secure research funding. A clear ability and passion for undergraduate education is essential. The incoming faculty member would join a committed team dedicated to the development and teaching of the Mathematical, Computational and Statistical Sciences Major (see https://mcs.yale-nus.edu.sg/) and Yale-NUS’s flagship Common Curriculum (see http://www.yale-nus.edu.sg/curriculum/common-curriculum). The appointee will be expected to begin duties in either January 2022 or August 2022. Faculty receive salaries that are on par with the most prestigious liberal arts colleges in the world, a substantial start-up grant as well as a yearly travel and research allowance, and are able to access additional funding from Yale-NUS, National University of Singapore, and Singapore’s Ministry of Education. Faculty are entitled to a 5-month sabbatical for every three years spent in the College. Some existing Faculty have joint appointments with relevant NUS Departments, and this can be explored for new hires on a case-by-case basis. Most faculty qualify for highly subsidized faculty housing, either on campus or a short walk away. Yale-NUS College is located in Singapore, a multicultural city of six million that is known for its high quality of life and sits at the heart of a vibrant region. Applications should be submitted via https://academicjobsonline.org/ajo/YaleNUS. Review of applications begins 15 September 2021 and continues until the positions are filled. Only shortlisted candidates will be notified. For general enquiries, please email: Enquiry_ScienceDiv@yale-nus.edu.sg. For academic enquiries, please email the Head of Studies (Mathematical, Computational and Statistical Sciences), Professor Robby Tan: robby.tan@yale-nus.edu.sg Yale-NUS
College achieves excellence through the diversity of its students, faculty, and
staff and by embracing inclusivity, equity, and global engagement. We encourage
applications by diverse individuals with a demonstrated commitment to
continually support these values. For more information about the College,
please visit https://www.yale-nus.edu.sg Candidates should understand that by sharing information with Yale-NUS, they authorise the College to use their personal data for the purposes of this application. The College will not use their data for other purposes and ensure that their data remains secure and confidential. |