Works under general direction to provide analysis and develops algorithms and software for clinical and/or basic research problems. Impacts data acquisition, management, and analysis in basic, translational, and clinical research, including clinical trials. The Deep Learning for Precision Health Lab (www.montillolab.org ), a part of the Biodata Engineering Program of the Biomedical Engineering department at the University of Texas Southwestern in Dallas,TX seeks a talented and motivated Data Scientist to support large-scale multimodal biomedical imaging and AI research initiatives. The successful candidate will play a key role in curating and analyzing multimodal datasets, preparing resources for foundation-model development, and supporting NIH-funded projects at the intersection of machine learning, neuroscience, and oncology. This is a full-time, long-term staff scientist position focused on technical excellence, reproducible data management, and collaborative research in a dynamic academic environment. Our lab's focus is on developing the theory and application of deep learning (DL) and causal modeling to elucidate treatment mechanisms, and to guide prognosis and treatment decisions with applications in neurological disorders and cancer therapy. To maximize AI's efficacy for biomedicine we develop new methods delivering: (1) trustworthy AI, (2) multimodal data fusion, (3) causal analysis, (4) and sample efficiency. We then apply these methods in (5) biomedical and neuroscience applications The successful applicant will contribute by (a) learning to apply advanced ML-based causal analysis to quantify mechanistic relationships in experimental data, (b) constructing reinforcement learning approaches to guide dynamic therapies, and (c) helping in foundation model development and downstream tailoring in biomedical projects. With cutting-edge computational infrastructure, access to leading neurology, neuroscience, and cancer experts, and an unparalleled trove of high dimensional imaging and multi-omic data, our machine learning lab is poised for success in these research endeavors.
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Job Type
Full-time
Career Level
Mid Level
Industry
Educational Services
Number of Employees
5,001-10,000 employees