For more than 60 years, the Lawrence Livermore National Laboratory (LLNL) has applied science and technology to make the world a safer place.
We have an opening for a Postdoctoral Researcher to conduct research in the areas of accelerated materials discovery, optimization, development and certification using machine learning and data analysis tools. You will actively participate with and be an integral member of an interdisciplinary team responsible for conducting and supporting research in application of machine learning, data and statistical analysis to chemistry and materials science. This position is in the Functional Materials Synthesis and Integration group of the Materials Science Division.
Conduct research in application of Machine Learning and data analysis to materials science domain to enable development and optimization of materials.
Contribute to the development of a focused research program aimed at leveraging advances in machine learning and big data tools for chemistry and materials science.
Independently develop methods for analyzing multimodal chemistry and materials science data using machine learning to predict future performance.
Contribute to and actively participate in the development of novel concepts applying machine learning to chemistry and materials science to meet sponsor needs in appropriate national security areas.
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.
Maintain and establish laboratory protocols.
Document research; publish papers in peer-reviewed journals, and present results within the DOE community and at conferences.
Perform other duties as assigned.
Lawrence Livermore National Laboratory
Recent PhD in Materials Science, Chemistry, Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics or related field.
Experience and 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, multimodal learning, natural language processing, ensemble methods, scalable online estimation, and probabilistic graphical models.
Experience in the application of one or more higher-level programming languages such as Python, Java/Scala, Matlab, R or C/C++.
Knowledge and experience with Machine Learning algorithm development and with deep learning model development using TensorFlow, PyTorch, Keras, Caffe or Theano.
Ability to develop independent research projects through publication of 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.
Experience in applying machine learning and data analytics to scientific domains including materials science and chemistry.
About Lawrence Livermore National Laboratory
Lawrence Livermore National Laboratory, a national security laboratory, provides transformational solutions to national security challenges.