Lawrence Livermore National Laboratory
Materials Science - Machine Learning - Postdoctoral Researcher
Lawrence Livermore National Laboratory, Livermore, California, United States, 94551
Materials Science - Machine Learning - Postdoctoral Researcher
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 important for continued success of the Laboratory’s mission.Pay Range$113,760 AnnuallyJob Description
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 important for continued success of the Laboratory’s mission.Pay Range$113,760 AnnuallyJob Description We have an opening for a
Postdoctoral Researcher - Machine Learning
to conduct research in cheminformatics and materials informatics. You will be part of an interdisciplinary team of computer scientists, materials scientists, and chemists applying existing and developing new machine learning techniques to accelerate the design and development of materials and organic molecules. This position is in in the Functional Materials Synthesis and Integration Group of the Materials Science Division.This position offers a hybrid schedule, blending in-person and virtual presence. You will have the flexibility to work from home 30% time.You willDevelop cutting-edge machine learning and data science methods to aide in the discovery of new molecular and polymeric compounds with targeted properties.Utilize machine learning and data science techniques to automate the extraction of chemical data, knowledge, and underlying chemistry-function relationships to guide improvements in material design.Adapt and improve upon existing traditional machine learning methods to be amenable to challenges in the domain of chemistry and materials science.Contribute to and actively participate in the development of novel concepts applying machine learning to chemistry and materials science to solve critical materials science challenges.Document research; publish papers in peer-reviewed journals, and present results within the DOE community and at conferences.Pursue independent but complementary research interests and interact with a broad spectrum of scientists internally and externally to the Laboratory.Collaborate with scientists in a multidisciplinary team environment to accomplish research goals.Perform other duties as assigned.Qualifications
Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. Citizenship.PhD in Chemical Engineering, Chemistry, Materials Science, Mathematics or related field.Experience in one or more higher-level programming languages such as Python, Java/Scala, Matlab, R or C/C++.Broad experience and fundamental knowledge of developing and applying algorithms in one or more of the following Machine Learning areas/tasks: deep learning, unsupervised feature learning, zero- or few-shot learning, active learning, reinforcement learning, natural language processing, multimodal learning, ensemble methods, scalable online estimation, and probabilistic graphical models.Experience with one or more deep learning libraries such as TensorFlow, PyTorch, scikit-learn, Keras, Caffe or Theano.Ability to develop independent research projects and publish in peer-reviewed literature.Proficient verbal and written communication skills as reflected in effective presentations at seminars, meetings and/or teaching lectures.Initiative and interpersonal skills with desire and ability to work in a collaborative, multidisciplinary team environment.Qualifications We DesireKnowledge of or experience with applying machine learning to scientific domains.Experience working with variety of types of input data for machine learning (images, molecules, text).Additional Information #LI-HybridPosition InformationThis is a Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date.Why Lawrence Livermore National Laboratory?Included in 2024 Best Places to Work by Glassdoor!Flexible Benefits Package401(k)Relocation AssistanceEducation Reimbursement ProgramFlexible schedules (*depending on project needs)Inclusion, Diversity, Equity and Accountability (IDEA) - visit https://www.llnl.gov/diversityOur core beliefs - visit https://www.llnl.gov/diversity/our-valuesEmployee engagement - visit https://www.llnl.gov/diversity/employee-engagementSecurity ClearanceThis position requires a Department of Energy (DOE) Q-level clearance. If you are selected, we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. Also, all L or Q cleared employees are subject to random drug testing. Q-level clearance requires U.S. citizenship.Pre-Employment Drug TestExternal applicant(s) selected for this position must 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.Wireless and Medical DevicesPer the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession. This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas. Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.How to identify fake job advertisementsPlease be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under “Find Your Job” of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdfEqual Employment OpportunityWe are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. 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.We invite you to review the Equal Employment Opportunity posters which include EEO is the Law and Pay Transparency Nondiscrimination Provision.Reasonable AccommodationOur 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 use our online form to submit a request.California Privacy NoticeThe 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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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 important for continued success of the Laboratory’s mission.Pay Range$113,760 AnnuallyJob Description
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 important for continued success of the Laboratory’s mission.Pay Range$113,760 AnnuallyJob Description We have an opening for a
Postdoctoral Researcher - Machine Learning
to conduct research in cheminformatics and materials informatics. You will be part of an interdisciplinary team of computer scientists, materials scientists, and chemists applying existing and developing new machine learning techniques to accelerate the design and development of materials and organic molecules. This position is in in the Functional Materials Synthesis and Integration Group of the Materials Science Division.This position offers a hybrid schedule, blending in-person and virtual presence. You will have the flexibility to work from home 30% time.You willDevelop cutting-edge machine learning and data science methods to aide in the discovery of new molecular and polymeric compounds with targeted properties.Utilize machine learning and data science techniques to automate the extraction of chemical data, knowledge, and underlying chemistry-function relationships to guide improvements in material design.Adapt and improve upon existing traditional machine learning methods to be amenable to challenges in the domain of chemistry and materials science.Contribute to and actively participate in the development of novel concepts applying machine learning to chemistry and materials science to solve critical materials science challenges.Document research; publish papers in peer-reviewed journals, and present results within the DOE community and at conferences.Pursue independent but complementary research interests and interact with a broad spectrum of scientists internally and externally to the Laboratory.Collaborate with scientists in a multidisciplinary team environment to accomplish research goals.Perform other duties as assigned.Qualifications
Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. Citizenship.PhD in Chemical Engineering, Chemistry, Materials Science, Mathematics or related field.Experience in one or more higher-level programming languages such as Python, Java/Scala, Matlab, R or C/C++.Broad experience and fundamental knowledge of developing and applying algorithms in one or more of the following Machine Learning areas/tasks: deep learning, unsupervised feature learning, zero- or few-shot learning, active learning, reinforcement learning, natural language processing, multimodal learning, ensemble methods, scalable online estimation, and probabilistic graphical models.Experience with one or more deep learning libraries such as TensorFlow, PyTorch, scikit-learn, Keras, Caffe or Theano.Ability to develop independent research projects and publish in peer-reviewed literature.Proficient verbal and written communication skills as reflected in effective presentations at seminars, meetings and/or teaching lectures.Initiative and interpersonal skills with desire and ability to work in a collaborative, multidisciplinary team environment.Qualifications We DesireKnowledge of or experience with applying machine learning to scientific domains.Experience working with variety of types of input data for machine learning (images, molecules, text).Additional Information #LI-HybridPosition InformationThis is a Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date.Why Lawrence Livermore National Laboratory?Included in 2024 Best Places to Work by Glassdoor!Flexible Benefits Package401(k)Relocation AssistanceEducation Reimbursement ProgramFlexible schedules (*depending on project needs)Inclusion, Diversity, Equity and Accountability (IDEA) - visit https://www.llnl.gov/diversityOur core beliefs - visit https://www.llnl.gov/diversity/our-valuesEmployee engagement - visit https://www.llnl.gov/diversity/employee-engagementSecurity ClearanceThis position requires a Department of Energy (DOE) Q-level clearance. If you are selected, we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. Also, all L or Q cleared employees are subject to random drug testing. Q-level clearance requires U.S. citizenship.Pre-Employment Drug TestExternal applicant(s) selected for this position must 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.Wireless and Medical DevicesPer the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession. This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas. Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.How to identify fake job advertisementsPlease be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under “Find Your Job” of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdfEqual Employment OpportunityWe are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. 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.We invite you to review the Equal Employment Opportunity posters which include EEO is the Law and Pay Transparency Nondiscrimination Provision.Reasonable AccommodationOur 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 use our online form to submit a request.California Privacy NoticeThe 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.
Receive tips & info on cleared job search, security clearances and career development.
#J-18808-Ljbffr