| A postdoctoral position is available at Brandeis University to work on geometric algorithms for machine learning (hosted by Tyler Maunu). Mathematical techniques include metric geometry, optimization, and stochastic differential equations. Potential research topics will lie at the intersection between optimal transport and machine learning, and may consider algorithms for embeddings, variational inference, or sampling. The successful candidate will join the Mathematics Department at Brandeis University (http://www.brandeis.edu/departments/mathematics/). The position is for 1 year, with a potential for extension contingent on funding and satisfactory progress. The postdoc will be able to participate in seminars and journal clubs, obtain mentoring experience, and has a potential for teaching opportunities.
First consideration will be given to applications received by February 15, 2022. Applications should be submitted through MathJobs.org and should include an AMS cover sheet, a curriculum vitae, a research statement, and three letters of recommendation. The expected start date is July 1, 2022 but is negotiable. Candidates should hold a Ph.D. in mathematics or a related topic, including statistics, computer science, or engineering, by the starting date, have an excellent track record of scholarship, and have experience in machine learning theory as well as programming experience in a relevant language, such as Python or Matlab.
Inquiries should be sent to Tyler Maunu at maunu@brandeis.edu with the subject heading "Postdoctoral Research Associate".
At Brandeis, we believe that diversity, equity, and inclusion are essential components of academic excellence. Brandeis University is an affirmative action, equal opportunity employer that is committed to creating equitable access and opportunities for applicants to all employment positions. Because diversity, equity, and inclusion are at the core of Brandeis’ history and mission, we value and are seeking candidates that represent a variety of social identities, including those that have been underrepresented in higher education, who possess skills that spark innovation, and who, through their scholarly pursuits, teaching, and/or service experiences, bring expertise in building, engaging, and sustaining a pluralistic, just, and inclusive campus community. |
finished (2021/12/16, finished 2022/06/17)