Computer, Computational & Stat Sciences

at  Los Alamos National Laboratory

MINIMUM JOB REQUIREMENTS:

• Currently enrolled in an accredited undergraduate degree program in any Computer Science or Mathematics (or related) discipline.
• Must be enrolled in at least 12 semester credit hours (or full-time equivalent).
• Must currently have and maintain a cumulative GPA of at least 3.0 on a 4.0 scale (or equivalent).

DESIRED QUALIFICATIONS:

• Computer programming (Python, C++, etc.) in support of scientific or engineering applications.
• Application of advanced mathematical methods to develop models of physical phenomena.
• Familiarity with cutting edge computational research in applications such as cybersecurity, artificial intelligence, machine learning, and quantum computing.
• Demonstrated ability to communicate (verbal and written) well in a professional scientific context; and Commitment to achieving results in a complex social and organizational setting.
  Location: This position will be located in Los Alamos, NM.

Come join the brightest minds at the most innovative R&D facility supporting our national security! The Computer, Computational and Statistical Sciences (CCS) Division is seeking undergraduate students (UGS) looking for a challenging internship. As a CCS UGS student, we will provide you with a mentor, a challenging project, and an opportunity to present your work and progress to colleagues. The projects will vary depending on your skills and interests and the Laboratory’s current needs. The CCS UGS program offers paid summer and year-round internships for undergraduate students in a variety of Computer Science, Mathematics, and Statistics projects. The GRA program provides mentoring, hands-on technical experience, and professional development opportunities through a normalized work plan complementing the student’s chosen area of study. You will work closely with one of four groups within the CCS Division.

• Computational Physics and Methods conducts research in numerical methods and algorithms, physical model development, and software engineering.
• Information Sciences engages in a wide variety of basic and applied research activities that are directly applicable to core needs.
• Statistical Sciences provides statistical reasoning and rigor to multidisciplinary scientific investigation and the development, application, and communication of cutting-edge statistical sciences research.
• Applied Computer Science is to be the vanguard for scientific simulations at extreme scale through the co-design of applications, algorithms, and architectures

Come join the brightest minds at the most innovative R&D facility supporting our national security! The Computer, Computational and Statistical Sciences (CCS) Division is seeking undergraduate students (UGS) looking for a challenging internship. As a CCS UGS student, we will provide you with a mentor, a challenging project, and an opportunity to present your work and progress to colleagues. The projects will vary depending on your skills and interests and the Laboratory’s current needs. The CCS UGS program offers paid summer and year-round internships for undergraduate students in a variety of Computer Science, Mathematics, and Statistics projects. The GRA program provides mentoring, hands-on technical experience, and professional development opportunities through a normalized work plan complementing the student’s chosen area of study. You will work closely with one of four groups within the CCS Division.

• Computational Physics and Methods conducts research in numerical methods and algorithms, physical model development, and software engineering.
• Information Sciences engages in a wide variety of basic and applied research activities that are directly applicable to core needs.
• Statistical Sciences provides statistical reasoning and rigor to multidisciplinary scientific investigation and the development, application, and communication of cutting-edge statistical sciences research.
• Applied Computer Science is to be the vanguard for scientific simulations at extreme scale through the co-design of applications, algorithms, and architectures.