Postdoctoral Research into Foundation Models for Scientific Data

at  Los Alamos National Laboratory

Job TitlePostdoctoral Research into Foundation Models for Scientific DataLocationLos Alamos, NM, USOrganization NameCCS-3/ Information SciencesMinimum SalaryMaximum Salary
What You Will Do
Los Alamos National Laboratory (LANL) is a world expert in scientific solutions for national security; come and be part of the next wave of machine learning applications for science! The Computer, Computational, and Statistical Sciences Division is seeking outstanding candidates for a postdoctoral research associate position in the development and analysis of large foundation models for scientific data. The position is available immediately.
You will work with a multi-institution and diverse team of scientists developing large multi-modal foundation models (consisting of at least one billion parameters or more) from scratch. The team will be using scientific data sets (data coming from scientific simulations, observational or experimental data) for creating large foundation models on LANL supercomputers and analyzing the created models for effectiveness.
You should have experience in large-scale machine learning methods and model training, a strong publication record, software development skills, an interdisciplinary research philosophy, and the ability to effectively communicate with researchers with varied backgrounds. As a postdoctoral research associate, you will be presented with the opportunity to publish results in high-impact peer-reviewed journals and to present at well-known conferences. The position is for two years, with a third year possible based on performance and funding.
What You Need
Minimum Job Requirements:
Technical Experience:
Recognized research experience in machine learning fundamentals, practical experience in training machine learning models (e.g., using PyTorch, TensorFlow etc.), strong programming and software development skills (e.g., using Python), and at least some experience coding for HPC clusters.
Communication:
Excellent presentation, oral, and written communication skills.
Publications
Track record of peer-reviewed publications and presentations in your home discipline.
Education/Experience: Ph.D. in Computer Science, Electrical Engineering, Applied Math, or related discipline, completed within the last 5 years. Applications from candidates who will earn their degree by the time of appointment are accepted.

Desired Qualifications:

• Experience with large language models or foundation models
• Experience with training Transformers from scratch
• Experience developing machine-learning software for HPC architectures
• Large data analysis and visualization skills

Work Environment:
Work Location: The work location for this position is onsite and located in Los Alamos, NM. All work locations are at the discretion of management.
Position commitment: Regular appointment employees are required to serve a period of continuous service in their current position in order to be eligible to apply for posted jobs throughout the Laboratory. If an employee has not served the time required, they may only apply for Laboratory jobs with the documented approval of their Division Leader. The position commitment for this position is 1 year.
Note to Applicants:
No applicant is expected to have all of the desired skills. Anyone who meets the education and minimum job requirements is encouraged to apply.
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 generous 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 (paid sick, vacation, and holidays)
• Onsite gyms and wellness programs
• Extensive relocation packages (outside a 50 mile radius)

Please refer the Job description for details