Los Alamos National Laboratory, Multiple HPC Intern Summer Opportunities

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For questions about internships and instructions on how to apply, please email HPCRecruits@lanl.gov


HPC Data Movement and Storage Team: Upcoming Student Project Opportunities

PROJECT: EMERGING STORAGE SYSTEM(S) EVALUATION

(Lead Mentor: Dominic Manno)

Storage systems are evolving as technology, such as flash, becomes economically viable. Vendors implementing cutting edge hardware solutions often approach LANL to help gain insight into how these systems could move into the real world (HPC applications). Work in this area includes potential modifications to filesystems, filesystem configuration/tuning, testing hardware, fixing bugs, finding bottlenecks anywhere in the stack in order to increase efficiency and make the storage system faster.

Preferred skills:

● Interest in HPC and storage systems
● Comfortable with computer hardware
● Strong analytical skills
● Benchmarking experience
● Experience with linux and scripting (bash, csh, Python, etc.)
● Comfortable with C programming

PROJECT: FILE SYSTEM(S) FEATURE AND TOOLSET EVALUATIONS

(Lead Mentor: Dominic Manno)

File systems evolve along with user requirements. New features are implemented to accommodate changing workloads and technology. LANL’s storage team must evaluate new features and their impact on HPC applications. This work will explore file system features, modifications to current build procedures/processes, and impact to LANL’s storage team metric collection tooling. Work in this area includes building source code (kernel included), configuring linux servers, configuring a basic distributed file system, benchmarking, experiment design, analysis of data, and scripting.

Preferred skills:

● Knowledge of and interest in filesystems
● Experience with Linux and Command Line Interface
● Experience with code build systems and software
● Interest in HPC and storage systems at scale
● Benchmarking experience

ABOUT THE HPC DATA MOVEMENT AND STORAGE TEAM:
The High Performance Computing (HPC) Data Storage Team provides vanguard production support, research, and development for existing and future systems that feed and unleash the power of the supercomputer. The Data Storage Team designs, builds and maintains some of the largest, fastest and most complex data movement and storage systems in the world, including systems supporting 100 Petabytes of capacity. We provide storage systems spanning the full range of tiers from the most resilient archival systems to the pinnacle of high-speed storage, including all-flash file systems and systems supplying bandwidth that exceeds a terabyte per second to some of the largest and fastest supercomputers in the world. Innovators and builders at heart, the Data Storage team seeks highly motivated, productive, inquisitive, and multi-talented candidates who are equally comfortable working independently as well as part of a team. Team member duties include: designing, building, and maintaining world-class data movement and storage systems; evaluating and testing new technology and solutions; system administration of HPC storage infrastructure in support of compute clusters; diagnosing, solving, and implementing solutions for various system operational problems; tuning file systems to increase performance and reliability of services; process automation.


HPC Platforms Team: Upcoming Student Project Opportunities

PROJECT: HPC CLUSTER REGRESSION
(Lead Mentor: Alden Stradling)

Building on work done by our interns this summer, we are continuing the process of adapting existing regression testing software to do system-level regression testing. Using the LANL- developed Pavilion2 framework in combination with Node Health Check (NHC) for more detailed information, our interns are moving the system from proof-of-concept in a virtualized test cluster to production-style systems to measure effectiveness and system performance impact, and to flesh it out as a running system. Also on the agenda is to make test creation and propagation simple, allowing regression detection to be added at the same time as fixes are made to the system.

Preferred skills

• Interest in HPC and modern infrastructure management at scale
• Problem solving and creativity
• Configuration Management
• Version Control
• Programming experience in bash, python or perl
• Strong background in UNIX and familiarity using CLI

About the HPC Platforms Team
The High Performance Computing (HPC) Platforms Team provides vanguard system and runtime support for some of the largest and fastest supercomputers in the world, including multi-petaop systems (e.g., the recently deployed 40 Peta operations per second Trinity Supercomputer). Troubleshooters and problem- solvers at heart, the HPC Platforms Team seeks highly motivated, productive, inquisitive, and multi-talented candidates who are equally comfortable working independently as well as part of a team. Team member duties include: system deployment, configuration, and full system administration of LANL’s world-class compute clusters; evaluating and testing new technology and solutions; diagnosing, solving, and implementing solutions for various system operational problems; system administration of HPC network infrastructure in support of compute clusters; diagnosing, solving, and implementing solutions for various system operational problems; system software management and maintenance, including security posture maintenance; tuning operating systems to increase performance and reliability of services; developing tools to support automation, optimization and monitoring efforts; interacting with vendors; and communicating and collaborating with other groups, teams, projects and sites.


HPC Design Group: Upcoming Student Project Opportunities

PROJECT: OPTIMIZING “SPACK CONTANERIZE” FOR USE WITH CHARLIECLOUD

(Lead Mentor: Tim Randles)

The Spack software package manager has the ability to output software build recipes as dockerfiles. These dockerfiles often require hand-editing to work well with Charliecloud. In this project you will work with the Charliecloud team at Los Alamos to identify common problems with Spack dockerfiles. You will then determine if these problems are best addressed by making changes to Charliecloud’s dockerfile support or if there are improvements that should be proposed to Spack’s containerize functionality. The intern will be expected to implement suggested changes. At the end of the summer the intern will present their work.

PROJECT: BUILDING A GITLAB TEST INFRASTRUCTURE USING THE ANSIBLE REPOSITORY

(Lead Mentor: Cory Lueninghoener)

Use Gitlab’s CI/CD pipeline and runner functionality to build an automated test infrastructure for checkins to our Git-backed Ansible repository. This would start out with getting familiar with Gitlab’s automated pipeline capabilities and running tasks on code checkin, and move on to simple linting tests that run each time a change is checked in. From there, it could move on to running larger test suites on VMs or in containers, all the way up to building and testing virtual clusters and tagging good cluster image releases.

About the HPC DES Group:
The High Performance Computing Design Group focuses on future technologies and systems related to HPC while providing technical resources when needed to the more production focused HPC Groups. Areas of focus include I/O and storage, future HPC architectures, system management, hardware accelerators, and reliability and resiliency. Production timescales of projects vary from weeks in the future for production deployments to 10 years or more for some of the reliability and future architecture work.


Where You Will Work:
Our diverse workforce enjoys a collegial work environment focused on creative problem solving, where everyone’s opinions and ideas are valued. We are committed to work-life balance, as well as both personal and professional growth. We consider our creative and dedicated scientific professionals to be our greatest assets, and we take pride in cultivating their talents, supporting their efforts, and enabling their successes. We provide mentoring to help new staff build a solid technical and professional foundation, and to smoothly integrate into the culture of LANL.

Los Alamos, New Mexico enjoys excellent weather, clean air, and outstanding public schools. This is a safe, low-crime, family-oriented community with frequent concerts and events as well as quick travel to many top ski resorts, scenic hiking & biking trails, and mountain climbing. The short drive to work includes stunning views of rugged canyons and mesas as well as the Sangre de Cristo mountains. Many employees choose to live in the nearby state capital, Santa Fe, which is known for world-class restaurants, art galleries, and opera.

About LANL:
Located in northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security. LANL enhances national security by ensuring the safety and reliability of the U.S. nuclear stockpile, developing technologies to reduce threats from weapons of mass destruction, and solving problems related to energy, environment, infrastructure, health, and global security concerns.

The High Performance Computing (HPC) Division provides production high performance computing systems services to the Laboratory. HPC Division serves all Laboratory programs requiring a world-class high-performance computing capability to enable solutions to complex problems of strategic national interest. Our work starts with the early phases of acquisition, development, and production readiness of HPC platforms, and continues through the maintenance and operation of these systems and the facilities in which they are housed. HPC Division also manages the network, parallel file systems, storage, and visualization infrastructure associated with the HPC platforms. The Division directly supports the Laboratory’s HPC user base and aids, at multiple levels, in the effective use of HPC resources to generate science. Additionally, we engage in research activities that we deem important to our mission.

Los Alamos National Laboratory, Supercomputer Institute Summer Internship Opportunity

By | News, SC2 jobs

PROGRAM OVERVIEW
The Supercomputer Institute is an intense, paid, 11-week, hands-on technical internship for people of all majors interested in the growing field of high-performance computing. You will obtain a thorough introduction to the techniques and practices of HPC; no HPS experience is required.

The program begins with two weeks of “boot camp”. Small teams of interns build, configure, test, and operate an HPC compute cluster starting from scratch, turning a head of equipment, cables, and electricity into a working mini-supercomputer that can run real HPC applications.

Next, the project phase begins. Teams of interns work under the guidance of HPC Division staff mentors on applied research and development projects that address real challenges currently faced by the division. Some projects use the mini-supercomputers built during boot camp, and others use existing LANL resources. These projects regularly influence the division as well as the field of high-performance computing.

Finally, teams present their accomplishments as a poster and technical talk to Laboratory management, staff, and fellow interns in an end-of-summer celebration of intern work.

The program runs June 1, 2021 – August 13, 2021.

View full job post here.

PROFESSIONAL DEVELOPMENT:
In addition to the technical portion of the program, interns also participate in fast-paced, focused professional development work, including:

  • Intense mentoring
  • Teamwork and professional collaboration
  • Resume writing and evaluation
  • Technical poster/presentation design and public speaking
  • Technical seminars on current HPC topics. Past seminars include high-speed networking, Linux containers,
  • parallel filesystems, facilities, and more.
  • Science lectures given by staff from across the Laboratory, from how the Mars Rover works to machine learning/ AI to black hole collisions.
  • Opportunities to sign up for tours of our world-class facilities, including the magnet lab, particle accelerator, million-core supercomputer, and ultra-cold quantum computer.

WHO IS ELIGIBLE TO APPLY:
The program is targeted to rising juniors or seniors, master’s students, and recent graduates with a bachelor’s or associate’s degree. Very highly qualified rising sophomores have been successful in the past, as well as occasional master’s graduates and Ph.D. students who can make a good case that they need hands-on practical training, rather than a research internship.

REQUIRED QUALIFICATIONS:
Interns must meet the following minimum requirements. If you are unsure whether you meet them, please ask us! We don’t want miss someone because they meet requirements in a way we did not anticipate.

  • Computer science, computer engineering, IT, or related experience/training.
  • Intermediate understanding of the Linux OS. For example, this might mean you have basic understanding of how an operating system works, some experience using Linux, and some knowledge of how Linux differs from desktop (e.g., Mac, Window) or phone OSes (Android, iOS).
  • Intermediate command line skills. You should have basic knowledge of the terminal using a shell such as tcsh or Bash. This doesn’t necessarily have to be on Linux (Macs also have a nice command line).
  • Scripting or programming experience of some kind.
  • Collegial, personable, plays well with others; the program is a team sport. Please note this does not mean you have to be “normal”; neurodiversity is encouraged.
  • Well-rounded and curious.
  • Can deal with reasonable deadlines. It’s a fast-paced program, but not high pressure.
  • Meets LANL undergraduate or graduate student program requirements, as applicable.

DESIRED QUALIFICATIONS:
In addition to the above, we’re looking for interns that also have some of the following skills. Note that few interns have all of them.

  • Strong communication skills (written and/or oral).
  • Interesting experience with Linux, hardware, networking, security, filesystems, etc.
  • HPC experience, whether sysadmin or user.
  • C or systems programming experience.
  • Interesting novel perspectives. Can you expand our horizons?

APPLICATION DEADLINE:
Deadline to apply is December 1, 2020.

HOW TO APPLY:
Apply via the instructions on this page. You’ll need to submit the following materials:

  • Current resume
  • Unofficial transcript, including GPA
  • Cover letter describing:
    • Your professional interests, experience, and goals
    • Why you are interested in the Supercomputer Institute
    • How you meet the minimum and desired skills above
    • What you hope to contribute to our team environment

ABOUT LOS ALAMOS:
Los Alamos is a small town in the mountains of northern New Mexico, located an elevation of 7,500 feet.

The town has an active intern community with various events such as free concerts. Outdoor activities are abundant, including hiking, camping, mountain biking, and rock climbing. Summers tend to be warm, and either dry or with afternoon monsoonal thunderstorms.

Stephen Timoshenko Distinguished Postdoctoral Fellowship at Stanford University

By | News, SC2 jobs

Stanford’s Mechanics and Computation Group (Department of Mechanical Engineering) is seeking applicants for a two-year term distinguished postdoctoral fellowship.

 

ABOUT THE FELLOWSHIP:

The Stephen Timoshenko Distinguished Postdoctoral Fellow will be given the opportunity to pursue independent research in the general area of solid mechanics, as well as to contribute to ongoing research in the Mechanics and Computation Group. 

QUALIFICATIONS:

  • Research activities should be in the field of solid mechanics interpreted broadly. 
  • The candidate should be aligned with interests in the group, which include additive manufacturing, micro- and nano-mechanics, and bio-mechanics, with an interest in machine learning as it applies to the field of computational mechanics. 
  • Candidates will be given opportunities to develop their teaching experience by designing and teaching a class in the mechanics curriculum. 
  • This position is primarily targeting candidates who are seeking an academic career in a leading research university.
  • Candidates are expected to show outstanding promise in research, as well as strong interest and ability in teaching. 
  • They must have received a Ph.D. prior to the start of the appointment, but not more than 2 years before. 

APPLICATION DEADLINE: 

Fellowship applications are accepted year-round, with deadlines on October 1, December 1, April 1, and July 1. 

  • Applications received before these dates will be reviewed together. 
  • This position will close as soon as an offer is made and has been accepted by a candidate.

HOW TO APPLY:

Send your application by email to Kelly Chu, kchu22@stanford.edu

  • Email subject: Stephen Timoshenko Distinguished Postdoctoral Fellow search
  • All documents attached to the email should be PDF (Portable Document Format).

Application documents:

  • Cover letter (one page)
  • Curriculum vitae
  • List of publications
  • Brief statements of proposed research (up to three pages) and teaching (one page) 
  • Names and contact information of three recommendation letter writers

EEO STATEMENT:

Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law. Stanford welcomes applications from candidates who bring additional dimensions to the University’s research and teaching missions.

Some resources on diversity and inclusion at Stanford:

Reducing lung cancer mortality through modeling and simulations

By | Feature, Research

Lung cancer remains the leading cause of cancer related mortality in the US, and globally, accounting for 1.8 million deaths annually. Many of these deaths are preventable by the implementation of prevention strategies, including tobacco control policies and lung cancer screening recommendations, and by improvements in lung cancer treatment.  In the US, these policies have generally been implemented based on the analysis and outcomes of the population as a whole, although data analyses have shown that smoking and lung cancer rates, and access to healthcare and interventions, vary significantly by education, income, and race/ethnicity.

The Cancer Intervention and Surveillance Modeling Network (CISNET) Lung Working Group (LWG), led by Rafael Meza, associate professor of Epidemiology from the School of Public Health and MICDE member, has been awarded a new $8.5M grant to investigate the synergistic impacts of tobacco control policies, lung cancer screening and treatment interventions in the US and in middle-income nations. For the past 15 years, the CISNET LWG has contributed to the development of US national strategies for reducing the lung cancer burden by quantifying, through modeling and simulation, the impact of tobacco control on smoking, lung cancer, and overall mortality, as well as the population benefits and harms of lung cancer screening. This new grant will allow the group to expand their work to consider the impact of treatment improvements, including targeted therapies and immunotherapies,  and the synergies between treatment and prevention interventions. It also will enable the researchers to continue their work in addressing smoking and lung cancer disparities. The consortium uses a comparative modeling approach, where multiple, but distinct, models use the same data inputs, and aim to answer a common question with different approaches. This allows the group to assess the strengths and weaknesses of the different models, and aid the decision making process.

Established in 2000, CISNET is a consortium of NCI-sponsored investigators who use modeling and simulation to improve their understanding of cancer control interventions in prevention, screening, and treatment and their effects on population trends in incidence and mortality. CISNET is committed to bringing the most sophisticated evidence-based planning tools to population health and public policy. These models have been used to guide public health research and priorities, and have aided the development of optimal cancer control strategies. Besides lung cancer, CISNET also includes breast, colon, cervical esophageal and prostate cancer groups.