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Position: Postdoc in Scientific Machine Learning

The Texas A&M Institute of Data Science (TAMIDS) has established its Scientific Machine Learning (SciML) Lab as part of a new initiative to develop knowledge, resources, and community around thematic areas of Data Science / Artificial Intelligence / Machine Learning, encompassing research, education, and outreach. TAMIDS supports each thematic Lab through a combination of seed funding for new research, effort from TAMIDS personnel, and support from TAMIDS programs to develop resources for education, training and research.

TAMIDS is seeking to recruit a postdoctoral research associate to join the SciML Lab multidisciplinary team, currently comprising six faculty drawn from the Colleges of Science and Engineering, researchers from TAMIDS and Texas A&M High Performance Research Computing, and associated graduate students.

Duties

The postdoc will undertake original high-quality research within the multidisciplinary collaborative groups in SciML Lab, produce publications, conference papers and other research outputs, and attend and present of research findings at appropriate conferences and meetings. They will promote the wider adoption of their research results within and beyond SciML Lab, through talks and short courses, developing software packages to implement their research results and providing consultancy on their usage to other researchers, and by contributing to SciML Lab online social media. They will assist with mentoring research students in the group and/or interdisciplinary student team projects.

Knowledge and Experience

The successful candidate will have PhD in Science or Engineering, with a disciplinary background in Computer Science, Electrical Engineering, Statistics, Mathematics or a discipline related to Machine Learning and Scientific Computation. They will have strong programming skills and demonstrated expertise in machine learning, together with the ability to work in multidisciplinary teams, good communication skills, and the ability to multi-task and work cooperatively with others. They will preferably have the following knowledge, skills, and abilities: advanced knowledge of contemporary machine learning methods and foundations; experience with high performance computing and numerical methods to solve science and engineering problems; strong programming skills including experience with Keras / TensorFlow / Python / Julia, together with strong interpersonal skills and the ability to cultivate and maintain strong working relationships with people of diverse backgrounds

How To Apply

Further specifics concerning the position and application procedures can be found on the Texas A&M Jobs Worksite.

Equal Employment Opportunity Statement

Texas A&M University is committed to enriching the learning and working environment for all visitors, students, faculty, and staff by promoting a culture that embraces inclusion, diversity, equity, and accountability. Diverse perspectives, talents, and identities are vital to accomplishing our mission and living our core values. The Texas A&M System is an Equal Opportunity / Affirmative Action / Veterans / Disability Employer committed to diversity. Texas A&M is dedicated to the goal of building an inclusive and culturally diverse researchers who are working in an environment of academic freedom and equality of opportunity

Contact and Enquiries

Prof. Ulisses Braga-Neto, SciML Lab Director, ulisses@tamu.edu