Computational & Data Science Research Spec. 2 or 3 - 139471

DEPARTMENT OVERVIEW:

The Computer Science and Engineering (CSE) department embodies the university's tradition of excellence as a world-class leader in computer science and engineering education and research. Ranked in the top 15 nationwide, the department is dedicated to research, education and overall excellence.

CSE has approximately 80+ faculty FTE, 20+ professional researchers, 50+ staff in career/casual titles, 150+ tutors, and 175+ TAs. There are over 1,700 undergraduate students enrolled in 3 majors, with annual enrollments of 25,000+. The department has a graduate education program with over 1,000 students (~350 PhD students and over 900 Master's students).

The Laboratory of Emerging Intelligence (LEI) is created to design and deploy next-generation AI (Artificial Intelligence) systems/platforms and is hosted by the Computer Science and Engineering (CSE) department. LEI will be the home for state-of-the-art research and development in next-generation AI systems and platforms.

POSITION OVERVIEW:

Under the direction of the faculty director and in collaboration with AI faculty and the Department Chair, the incumbent will advise on and resolve complex research and technology projects/issues, present research and technical briefings to senior management, faculty and students. The incumbent will contribute to the research and technical direction in one or more technical specialties, and they will perform advanced research and technology development to contribute to design of future AI systems. The incumbent may also represent the organization at national and international meetings, conferences and committees.

• Occasional evenings, weekends and overtime may be required.

Requirements for the Computational and Data Science Research Specialist level 2 RP:

• Bachelor's degree in Computer Science or Data Science or other fields with computer science or equivalent specialization. Demonstrated experience (typically 2-5 years exp.) in designing systems that enable end-user applications is required.

• Master's degree or higher degree in Computer Science or Data Science or other fields with computer science or equivalent specialization or equivalent experience in research and development in the area of AI is preferred.

• Working knowledge of applications programming and web development, databases and data systems, statistical methods and tools, and modern biology and applicable field of research.

• Demonstrated working knowledge of one of the following: Scalable systems, distributed systems, or systems performance.

• Strong knowledge of principles of modern system design and demonstrated experience associated with one or more of the following: AI system design, testing, evaluation, AI models, software development.

• Strong knowledge of AI software and systems as well as AI models.

• Knowledge of specific technologies including Python programming, cloud computing, interacting with commercial LLMs, and React programming.

• Strong knowledge of best practices in software engineering, such as code reviews, source code control, unit tests, integration tests.

• Exceptional ability to solve unusual or non-standard algorithmic problems and strong knowledge of algorithms taught in modern CS curricula.

Requirements for the Computational and Data Science Research Specialist level 3 RP:

• Bachelor's degree in Computer Science or Data Science or related area with computer science experience and experience with designing systems that enable end-user applications or equivalent specialization and/or experience/training.

• Master's degree or PhD in Computer Science or Data Science or related area with computer science experience or equivalent specialization and/or equivalent experience in research and development in the area of AI is preferred.

• 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.

• Experience with designing systems that enable end-user applications.

• Experience with research and technology in multiple aspects of creating software platforms and AI programming environments.

• Intermediate knowledge of HPC / data science / CI. Demonstrated skills in Artificial Intelligence, Natural Language Processing, Machine Learning systems and software systems.

• 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.

• Experience with software and platform architecture/development, with relevant domain science knowledge where applicable, to design, develop and deliver the AI applications, platforms and systems.

• 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 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.

Requirements for level 2 and 3:

• Proven ability to successfully work on multiple concurrent projects.

• Demonstrated experience and ability to collaborate effectively with all levels of staff; technical, students, faculty and administrators

• Demonstrated ability to regularly interface with management.

• 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.

• Demonstrated ability to contribute research and technical content to grant proposals.

• Job offer is contingent upon satisfactory clearance based on Background Check results.