Los Alamos National Security LLC
Sparse Neural Network Design Post-Doctoral Research Associate(s)
Los Alamos National Security LLC, Los Alamos, New Mexico, us, 87545
What You Will Do
The Applied Computer Science Group (CAI-1), within the Computing and AI Division (CAI), is seeking 1-2 highly motivated postdoctoral researchers to drive the research and development of novel sparse neural networks. The position(s) will be funded through the Department of Energy (DOE) Office of Science (SC) Advanced Scientific Computing Research (ASCR) program. The position is for a two-year term with the potential for impactful contributions to basic and applied neural network research. The broader collaboration for this project includes mathematicians at CU Boulder and Boston University. As a postdoctoral researcher, you will: Hand write custom sparse neural networks from scratch and perform computational experiments designed by mathematicians on the team. Interface with mathematicians and applied computer scientists to demonstrate the viability of novel neural networks on challenging benchmark datasets/problems, using cutting-edge high-performance computing platforms. Have opportunities to publish in leading peer-reviewed journals and present research at conferences, and to visit academic collaborators at CU Boulder and Boston University. What You Need
Minimum Job Requirements: A Ph.D. in Mathematics, Computer Science, Statistics, or a closely related field, earned within the last 5 years. Demonstrated research excellence, as evidenced by a strong publication record in one or more of the following areas: random matrix theory, stochastic processes, neural networks, machine learning, and sparse data structures. Proficiency in scientific programming, preferably in Python or C/C++. Strong communication skills, both written and oral, demonstrated through publications and the cover letter. Desired Qualifications Familiar with mathematical and coding aspects of neural networks. Contributions to prominent open source machine learning software projects, experience performing code reviews, and experience working in a team software development setting. Evidence of competitive excellence in machine learning (e.g., Kaggle competition rankings) and/or mathematics. Work Location
The work location for this position is onsite and located in Los Alamos, NM Education/Experience
A Ph.D. in Mathematics, Computer Science, Statistics, or a closely related field, earned within the last 5 years. Note to Applicants
For questions about this position, please contact Navamita Ray at nray@lanl.gov or Tyler Reddy at treddy@lanl.gov. Applicants should include a curriculum vitae (CV), a cover letter describing research interests and career goals, and contact information for two references. Please submit application materials directly through the LANL jobs website. Due to federal restrictions contained in the current National Defense Authorization Act, citizens of the People\u2019s Republic of China—including the special administrative regions of Hong Kong and Macau—as well as citizens of the Islamic Republic of Iran, the Democratic People\u2019s Republic of Korea (North Korea), and the Russian Federation, who are not Lawful Permanent Residents (green card holders) are prohibited from accessing facilities that support the mission, functions, and operations of national security laboratories and nuclear weapons production facilities, which includes Los Alamos National Laboratory. Where You Will Work
Located in beautiful northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security. Our benefits package includes: PPO or High Deductible medical insurance with the same large nationwide network Dental and vision insurance Free basic life and disability insurance Paid maternity and parental leave Award-winning 401(k) (6% matching plus 3.5% annually) Learning opportunities and tuition assistance Flexible schedules and time off (PTO and holidays) Onsite gyms and wellness programs Extensive relocation packages (outside a 50 mile radius) Additional Details
Directive 206.2 - Employment with Triad requires a favorable decision by NNSA indicating the employee is suitable under NNSA Supplemental Directive 206.2. This requirement applies only to citizens of the United States. Foreign nationals are subject to a similar requirement under DOE Order 142.3A. Position does not require a security clearance. Selected candidates will be subject to drug testing and other pre-employment background checks. New-Employment Drug Test: The Laboratory requires successful applicants to complete a new-employment drug test and maintains a substance abuse policy that includes random drug testing. Although New Mexico and other states have legalized the use of marijuana, use and possession of marijuana remain illegal under federal law. A positive drug test for marijuana will result in termination of employment, even if the use was pre-offer. Equal Opportunity: Los Alamos National Laboratory is an equal opportunity employer and supports a diverse and inclusive workforce. All employment practices are based on qualification and merit, without regard to race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation or preference, marital status or spousal affiliation, physical or mental disability, medical conditions, pregnancy, status as a protected veteran, genetic information, or citizenship within the limits imposed by federal laws and regulations. The Laboratory is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process. To request such an accommodation, please send an email to applyhelp@lanl.gov or call 1-505-665-4444 option 1. How to Apply: Login to Your Account to Complete the Application Process. Click the Vacancy Name number (in blue) to view any job\'s details. Click Apply or Add to Basket to apply later. Tip: To apply for a job or save your basket, you must have a LANL jobs account. If you experience any technical issues, please email applyhelp@lanl.gov for assistance.
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The Applied Computer Science Group (CAI-1), within the Computing and AI Division (CAI), is seeking 1-2 highly motivated postdoctoral researchers to drive the research and development of novel sparse neural networks. The position(s) will be funded through the Department of Energy (DOE) Office of Science (SC) Advanced Scientific Computing Research (ASCR) program. The position is for a two-year term with the potential for impactful contributions to basic and applied neural network research. The broader collaboration for this project includes mathematicians at CU Boulder and Boston University. As a postdoctoral researcher, you will: Hand write custom sparse neural networks from scratch and perform computational experiments designed by mathematicians on the team. Interface with mathematicians and applied computer scientists to demonstrate the viability of novel neural networks on challenging benchmark datasets/problems, using cutting-edge high-performance computing platforms. Have opportunities to publish in leading peer-reviewed journals and present research at conferences, and to visit academic collaborators at CU Boulder and Boston University. What You Need
Minimum Job Requirements: A Ph.D. in Mathematics, Computer Science, Statistics, or a closely related field, earned within the last 5 years. Demonstrated research excellence, as evidenced by a strong publication record in one or more of the following areas: random matrix theory, stochastic processes, neural networks, machine learning, and sparse data structures. Proficiency in scientific programming, preferably in Python or C/C++. Strong communication skills, both written and oral, demonstrated through publications and the cover letter. Desired Qualifications Familiar with mathematical and coding aspects of neural networks. Contributions to prominent open source machine learning software projects, experience performing code reviews, and experience working in a team software development setting. Evidence of competitive excellence in machine learning (e.g., Kaggle competition rankings) and/or mathematics. Work Location
The work location for this position is onsite and located in Los Alamos, NM Education/Experience
A Ph.D. in Mathematics, Computer Science, Statistics, or a closely related field, earned within the last 5 years. Note to Applicants
For questions about this position, please contact Navamita Ray at nray@lanl.gov or Tyler Reddy at treddy@lanl.gov. Applicants should include a curriculum vitae (CV), a cover letter describing research interests and career goals, and contact information for two references. Please submit application materials directly through the LANL jobs website. Due to federal restrictions contained in the current National Defense Authorization Act, citizens of the People\u2019s Republic of China—including the special administrative regions of Hong Kong and Macau—as well as citizens of the Islamic Republic of Iran, the Democratic People\u2019s Republic of Korea (North Korea), and the Russian Federation, who are not Lawful Permanent Residents (green card holders) are prohibited from accessing facilities that support the mission, functions, and operations of national security laboratories and nuclear weapons production facilities, which includes Los Alamos National Laboratory. Where You Will Work
Located in beautiful northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security. Our benefits package includes: PPO or High Deductible medical insurance with the same large nationwide network Dental and vision insurance Free basic life and disability insurance Paid maternity and parental leave Award-winning 401(k) (6% matching plus 3.5% annually) Learning opportunities and tuition assistance Flexible schedules and time off (PTO and holidays) Onsite gyms and wellness programs Extensive relocation packages (outside a 50 mile radius) Additional Details
Directive 206.2 - Employment with Triad requires a favorable decision by NNSA indicating the employee is suitable under NNSA Supplemental Directive 206.2. This requirement applies only to citizens of the United States. Foreign nationals are subject to a similar requirement under DOE Order 142.3A. Position does not require a security clearance. Selected candidates will be subject to drug testing and other pre-employment background checks. New-Employment Drug Test: The Laboratory requires successful applicants to complete a new-employment drug test and maintains a substance abuse policy that includes random drug testing. Although New Mexico and other states have legalized the use of marijuana, use and possession of marijuana remain illegal under federal law. A positive drug test for marijuana will result in termination of employment, even if the use was pre-offer. Equal Opportunity: Los Alamos National Laboratory is an equal opportunity employer and supports a diverse and inclusive workforce. All employment practices are based on qualification and merit, without regard to race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation or preference, marital status or spousal affiliation, physical or mental disability, medical conditions, pregnancy, status as a protected veteran, genetic information, or citizenship within the limits imposed by federal laws and regulations. The Laboratory is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process. To request such an accommodation, please send an email to applyhelp@lanl.gov or call 1-505-665-4444 option 1. How to Apply: Login to Your Account to Complete the Application Process. Click the Vacancy Name number (in blue) to view any job\'s details. Click Apply or Add to Basket to apply later. Tip: To apply for a job or save your basket, you must have a LANL jobs account. If you experience any technical issues, please email applyhelp@lanl.gov for assistance.
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