Job Location: Livermore, CA
Company Description
Join us and make YOUR mark on the World!
Are you interested in joining some of the brightest talent in the world to strengthen the United States’ security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.
We are committed to a diverse and equitable workforce with an inclusive culture that values and celebrates the diversity of our people, talents, ideas, experiences, and perspectives. This is essential to innovation and creativity for continued success of the Laboratory’s mission.
Job Description
We have openings for Postdoctoral Researchers to join our interdisciplinary team supporting a variety of application areas such as Bioscience, Cyber Security, Climate Modelling, Energy Systems and Advanced Manufacturing. Qualified candidates should have a strong foundation in theoretical and applied statistics as well as a background in a scientific discipline providing underlying skills in data analytic techniques. While supporting applied research projects, selected candidates will be provided mentorship and practical training to develop depth and breadth in machine learning techniques as well as gain exposure to a variety of application areas. These positions are in the Computational Engineering Division (CED) within the Engineering Directorate.
In this role you will
- Conduct research on statistical machine learning models for small datasets, Bayesian models for high-dimensional data and recommender systems.
- Develop and implement machine learning algorithms for testing and validation on biological data.
- Conduct data processing efforts, including but not limited to understanding the data through the use of visualization and statistical methods, cleaning/organizing the data, and applying state-of-the-art Machine Learning algorithms to real-world science and national security applications.
- Conduct paper/code surveys of state-of-the-art Machine Learning algorithms relevant to the problem being addressed.
- Contribute to research efforts in Machine Learning to enable development of new state-of-the-art algorithms for Laboratory problem domains.
- Conduct experiments, training and validating new state-of-the-art Machine Learning algorithms for Laboratory problem domains.
- Contribute to the integration of algorithms within larger programmatic systems that require these capabilities.
- Participate in interactions with inter-organizational contacts and/or external customers.
- Assist in representing the organization by providing input on technical issues for specific projects including preparing and presenting technical reports.
- Research, develop, and apply solutions to moderately complex Machine Learning problems of programmatic interest.
- Balance multiple priorities of partners to ensure deadlines are met, while working independently with minimal direction within scope of the assignment.
- Contribute to research proposals.
- Perform other duties as assigned.
Qualifications
- PhD in Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics, or another technical discipline providing an underlying skillset in data analysis and Machine Learning techniques.
- Fundamental knowledge of Bayesian methods and statistical mathematics.
- Fundamental knowledge of and/or experience developing and applying algorithms in one or more of the following Machine Learning areas/tasks: deep learning, representation learning, zero- or few-shot learning, active learning, reinforcement learning, natural language processing, ensemble methods, statistical modeling and inference (e.g., probabilistic graphical models, Gaussian processes, or nonparametric Bayesian methods).
- Experience in the broad application of one or more higher-level programming languages such as Python, Java, Scala, or C/C++.
- A history of publications in selective peer-reviewed conferences and/or journals.
- Ability to work independently under general direction within the scope of an assignment and use sound judgment in determining methods, techniques, and evaluation criteria.
- Proficient verbal and written communication skills to collaborate in a team environment, publish and present technical ideas at top-tier Machine Learning workshops or conferences and journals.
Qualifications We Desire.
- Familiarity with deep learning tools like PyTorch or TensorFlow.
- A background in the biological sciences that includes familiarity with biological protocols, terminology, and methods.
- Experience applying statistical and/or machine learning methods to biological data.
- A history of publications related machine learning and/or the biological sciences.
- Experience working in or collaborating with a biological laboratory known for high quality research.
Additional Information
All your information will be kept confidential according to EEO guidelines.
Position Information
This is a Postdoctoral appointment with the possibility of extension to a maximum of three years. Eligible candidates are those who have been awarded a PhD at time of hire date.
Why Lawrence Livermore National Laboratory?
- Included in 2022 Best Places to Work by Glassdoor!
- Work for a premier innovative national Laboratory
- Comprehensive Benefits Package
- Flexible schedules (*depending on project needs)
- Collaborative, creative, inclusive, and fun team environment
Learn more about our company, selection process, position types and security clearances by visiting our Career site.
Security Clearance
None required. However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process. This process includes completing an online background investigation form and receiving approval of the background check. (This process does not apply to foreign nationals.) For additional information, please see DOE Order 472.2.
Pre-Employment Drug Test
External applicant(s) selected for this position will be required to pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.
Equal Employment Opportunity
LLNL is an equal opportunity employer that is committed to providing candidates and employees with a work environment free of discrimination and harassment. We value and hire a diverse workforce as it is a vital component of our culture and success. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.
LLNL invites you to review the Equal Employment Opportunity posters which include EEO is the Law and Pay Transparency Nondiscrimination Provision.
Reasonable Accommodation
At LLNL, our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory. If you need a reasonable accommodation during the application or the recruiting process, please submit a request via our online form.
California Privacy Notice
The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.
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