Post-Doctoral Position in Machine Learning at the Center for Informatics and Computational Science (CICS) at the University of Notre Dame - Posted 6/19/2018
A post-doctoral position is available starting this fall or soon thereafter. The research efforts at CICS center around the development of innovative machine learning techniques as applied to predictive modeling of complex systems in engineering and the sciences.
We are interested in individuals with (1) Strong analytical, algorithmic, scientific computing and coding skills (2) Ability to comprehend latest machine learning articles, learn new techniques quickly and implement in PyTorch or TensorFlow (3) Experience in at least one of the following aspects of Machine Learning: deep learning, probabilistic Bayesian inference, probabilistic graphical models, Gaussian Processes, supervised and unsupervised learning, high-dimensional uncertainty quantification, etc. (4) Team orientation and (5) Potential to lead a research direction on physics guided machine learning and a team of PhD students.
Candidates should have a Ph.D. by the time of appointment in Computer Science/Informatics, Computational Mathematics or Statistics or any Engineering discipline.
Interested candidates should apply by emailing Prof. Nicholas Zabaras (email@example.com) and include (in PDF format):
- CV with the names of up to three references
- Statement of research experience, interests and goals
- Up to 3 indicative publications/preprints
Further details about the position are available upon request. Evaluation of applicants will start immediately and continue until the position is filled. Compensation levels are competitive based on prior background and experience.
The University of Notre Dame seeks to attract, develop, and retain the highest quality faculty, staff and administration. The University is an Equal Opportunity and affirmative action employer with a strong commitment to fostering a culturally diverse atmosphere for faculty, staff and students. Women and minorities are encouraged to apply.