DESCRIPTION The mission of the newly founded Data Science Institute is to advance the scientific foundations for this exciting new field, and to support education and training of students who will be the new leaders in this area. Digital data have emerged as central to addressing critical societal needs and enhancing the quality of life in the coming decades. Data science touches virtually all aspects of life on our planet. At the campus level, UC San Diego already has tremendous strength in this area, ranging across all segments of the university. For this reason, the Institute has been established as an independent unit that works collaboratively with schools, divisions, departments, centers, and faculty and students across the entire campus. The Institute is directed by the Director, who reports to an Oversight Committee chaired by the Chancellor. The Institute will be the administrative home for the newly established undergraduate B.S. major and minor in Data Science, and will work with departments and the Academic Senate to create additional graduate programs in data science. The institute will support collaborations between researchers across campus and will also provide critical resources to support innovation in data science. The incumbent will apply skills as a seasoned, experienced Computer Science (CS) and Physics research professional to find the best combination points between CS and Physics, such as analyzing and exploring the deep residual networks (e.g., ResNet and Transformer) through the neural ODE perspective. Knowledge and techniques in computer science, data science, machine learning, physics, numerical analysis, etc., are required. This position requires professional programming skills for medium-sized projects or portions of larger projects. The incumbent will develop and optimize a variety of modules for an optimal control of deep neural network models following principled, scientific ways to conduct experiments and collect results. The incumbent will also formulate proofs and theories towards understanding the deep neural networks. This position focuses on open-ended data science research, residing at the intersection among machine learning, data mining, and physics. It also includes responsibilities for writing research papers, mentoring undergraduate students and/or junior master students. Under the direction of the PI, this position exercises independent research judgment in developing methods, techniques, guidelines and evaluation criteria for obtaining results on project activities, milestones, and deliverables, showing in-depth ability to successfully work on concurrent projects and advanced skills in independently resolving complex data mining problems. The position frequently works on extremely complex problems that require critical thinking, problem solving, and careful analysis of unique scientific issues without precedent and/or structure. QUALIFICATIONS Intermediate knowledge of HPC / data science / CI. Intermediate knowledge of deep residual networks, including not but limited to ResNet, Transformers, and Recurrent Neural Networks. Advanced skills, and demonstrated experience associated with one or more of the following: HPC hardware and software power and performance analysis and research, design, modification, Implementation and deployment of HPC or data science or CI applications and tools. Advanced skills in leveraging GPU servers to conduct scientific computing, such as training multiple deep neural models at the same time on the cloud server without running any terminal on the local machine. Proven skills and experience in independently resolving broad computing / data / CI problems using introductory and / or intermediate principles. Proven ability to understand research computing / data / CI needs, mapping use cases to requirements and how systems / software / infrastructure can support those needs and meet the requirements. Demonstrated ability to develop and implement such solutions. Experience with remote servers is a must. Must be familiar with tools like SSH, tmux, etc., as well as deep learning frameworks, such as pytorch. Intermediate knowledge of physics and numerical analysis. Bachelor's degree in Computer/Computational/Data Science/Physics/Astronomy or Domain Sciences with computer / computational / data specialization or equivalent experience. Master's degree in Computer/Computational/Data Science/Physics/Astronomy or Domain Sciences with computer/computational/data specialization or equivalent experience preferred. SPECIAL CONDITIONS Job offer is contingent upon satisfactory clearance based on Background Check results.
