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research, preferably with 3D modelling skills. ¿ Foundational expertise in machine learning and big data analytics Job Summary Postdoctoral Researchers support teams of KSU faculty and students
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causal analytical foundations of mass transit system performance. The research is expected to contribute both novel methodological advances in statistical modelling, causal inference, and machine learning
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complex chemistry, molecular metal compounds, homogeneous metal catalysis, organic synthesis, mechanochemistry of metals, as well as experience in analytical techniques including NMR, PXRD, HRMS and ICP-MS
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, throughout the project development period. Desirable requirements: Previous experience in forensic science, food traceability and authentication, and application of nuclear analytical methods; experience in
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experience of mixed phase numerical or analytical flow modelling / solid mechanics / material characterization. Experience of analysing experimental data is highly desirable. You should have a record of
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, and range from applying methods developed in the lab to existing patient cohorts, to developing entirely new assays and analytical approaches. We study a wide variety of cancer types, with major focuses
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pharmacoepidemiology and healthcare analytics experience (Medicaid, Medicare, commercial, and EHR populations). Proficiency in R, Python, and SQL. City: New Brunswick State: NJ Location: Rutgers University - New
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models in Argonne’s GREET model and related analytical tools. The appointee will evaluate current and emerging production pathways, including lithium production from brines and hard-rock resources, lithium
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advanced characterization techniques (e.g., XRD, SEM-EDX, TEM, BET, TGA, XPS, …). Strong analytical thinking, problem-solving skills, and a creative approach to research challenges. Excellent English
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analytical and sensing instrumentation, partly in cooperation with Faculty Centers. It comprises nanomicroscopic techniques, electrochemical techniques, mass-sensitive measuring science and molecular