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discipline. Experience using Python to develop and implement ML and Deep Learning model architectures. Developing applications for geospatial data analysis Developing applications for computer vision
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initiatives to align college technology services with institutional priorities, as well as create long-term plans for the college’s information technology, media services and distance learning. The most
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using artificial intelligence and machine learning. Use technical expertise to advise on procedure changes and platform functionality that support achieving CE&C’s outcome goals. Manage and maintain
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technology modernization in higher education experience, strong product and project management skills, a proven ability to foster productive cross-campus partnerships, and a deep understanding of academic
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learning and engagement. Your skills will make a difference. You’ll be working for a university that is internationally recognized for its academic programs and research. Your work will have a direct impact
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. Preferred Qualifications Strong interest in pursuing a Ph.D. in a related discipline. Proficiency in programming languages such as Python (Preferred) or R. Experience in data analysis, machine learning, deep
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options for medical and childcare expenses Robust free training access through LinkedIn Learning plus professional conference opportunities. Tuition assistance Expansive employee discount program including
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language models for materials science, 4. Optimization in materials synthesis systems and autonomous high throughput discovery, 5. Deep learning in materials big data. Both experimental and computational
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throughput discovery, 5. Deep learning in materials big data. Both experimental and computational research activities will be considered across a board range of existing and emerging topics in materials
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training access through LinkedIn Learning plus professional conference opportunities Tuition assistance Expansive employee discount program including athletic tickets Free access to UT Austin's libraries and