Sort by
Refine Your Search
-
energy supply systems, multi-objective and stochastic optimization, advanced statistical analysis, and data visualization. This position offers the opportunity to work with a multidisciplinary team of
-
device-relevant properties Design active learning, Bayesian optimization, uncertainty-aware modeling, and other adaptive experimental design workflows to guide experiments and improve data efficiency in
-
diverse data sets, including trade, political, economic, and social metrics to identify global risks that impact sourcing strategies essential for achieving economic and climate objectives. Key
-
model classifiers (PLS-DA, random forest, neural network, etc) towards unraveling materials structure-function relationships, and are familiar with optimization approaches such as genetic search, Bayesian
-
objectives (e.g. spin characterization of host materials, silicon carbide synthesis for quantum information science, etc.). Collaboration is a cornerstone of our approach, and as such, the candidate will work
-
effectively within an interdisciplinary team of chemists, physicists, and materials scientists to accomplish research objectives. 4. Strong analytical and problem-solving skills, with the ability to interpret
-
with internal and external research partners to advance project objectives and meet program milestones Analyze experimental data and prepare reports, technical presentations, and updates for internal
-
of transportation including off-road, rail & marine applications too. These projects involve close collaboration with industrial and academic partners, and engagement with multidisciplinary project teams
-
). Skilled oral and written communication skills. Proven track record showing the ability to carry out independent and collaborative research in a multidisciplinary team while meeting project deliverables and
-
scientific problem solving as evidenced by publications and recommendations. Proven track record showing the ability to carry out independent and collaborative research in a multidisciplinary team while