CMPTL & DATA SCI RSH SPEC 3 RP

CMPTL & DATA SCI RSH SPEC 3 RP

University of California San Francisco - 4.1 San Francisco, CA Job Details Full-time 14 hours ago Qualifications Technical writing for researchers Content creation for technical audiences Research proposal writing Requirements design High-performance computing clusters Research industry grant writing Requirements analysis Technical research projects Systems analysis

Full Job Description Job Summary:

Involves a hybrid of multiple computational / data / Cyberinfrastrcture (CI) dominated fields such as, but not limited to, bioinformatics, geological information services (GIS), data analytics, and computational chemistry. Applies computational, computer science, data science and cyber infrastructure (CI) research and development principles, with relevant domain science knowledge, to perform research and technology integration and development. Responsibilities include research, design, development, analysis, operation, and support of high performance computing (HPC) and data science research, software, tools and hardware resources. Develops data algorithms and performs computations, statistical analyses, interpretation and reporting of research. This specialty / function exists for those positions whose primary responsibility is to do research and use computational and data science technology as a tool to accomplish the research.

Department Description:

In the Department of Psychiatry & Behavioral Sciences in the School of Medicine, the Neuroimaging Scientist will work closely with the Neuroimaging Technology Research Center (NTRC) scientific and technical directors, collaborating with a multidisciplinary team of experts. This team supports multiple projects aimed at enhancing our understanding and developing innovative treatment approaches for a range of neuropsychiatric conditions, from major depression to chronic pain. The Neuroimaging Scientist will bring expertise that will integrate neuroimaging data with behavioral and physiological monitoring, leveraging advanced neuromodulation technologies.

Required Qualifications:

Bachelor's degree in Computer / Computational / Data Science, or Domain Sciences with computer / computational / data specialization or equivalent experience Minimum of 3 years of related experience Intermediate knowledge of HPC / data science / CI 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 Demonstrated ability to regularly interface with management Demonstrated ability to contribute research and technical content to grant proposals Demonstrated effective communication and interpersonal skills. Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization and to external research and education audiences Proven skills and experience in independently resolving broad computing / data / CI problems using introductory and / or intermediate principles Self-motivated and works independently and as part of a team. Able to learn effectively and meet deadlines Thorough experience working in a complex computing / data / CI environment encompassing all or some of the following: HPC, data science infrastructure and tools / software, and diverse domain science application base Proven ability to successfully work on multiple concurrent projects 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 Demonstrated broad experience in one or more of the following: optimizing, benchmarking, HPC performance and power modeling, analyzing hardware, software, and applications for HPC / data / CI Demonstrated experience and ability to collaborate effectively with all levels of staff; technical, students, faculty and administrators