11 Environment Postdoctoral positions at Brookhaven National Laboratory in united-states-of-America
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utilizes advanced capabilities for studies of Nanomaterials in Operando Conditions for characterizing materials and reactions at the atomic scale in real-world environments. Position Description: The CFN is
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the Department of Energy Office of Biological and Environmental Research, this position will help develop a "Biopreparedness Research Virtual Environment" (BRaVE) platform to address current and emerging
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. We offer a supportive work environment and the resources necessary for you to succeed. Essential Duties and Responsibilities: * Develop a coherent X-ray scattering workflow for high-throughput, high
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Office 365 (Word, Excel, PowerPoint), SharePoint Ability to work collaboratively in a team environment. Ability to travel as required for project work and laboratory representation. Clear and concise oral
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communication and interpersonal skills to be able to interact effectively with a diverse group of scientists, engineers, and technical staff. * Self-motivated and able to work in a team environment. Preferred
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international venues. Work and communicate effectively in a team-oriented environment. Required Knowledge, Skills, and Abilities: Ph.D. degree in meteorology, atmospheric science, or a closely related field
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workplace environment Required Knowledge, Skills, and Abilities: PhD in nuclear or particle physics or related discipline Knowledge of particle detector concepts Experience with high energy programing
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) and the Hard X-ray Nanoprobe Beamline (HXN). Brookhaven National Laboratory and the Energy and Photon Sciences Directorate are committed to your success. We offer a supportive work environment and the
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synthesize magnetic van der Waals heterostructures and study them with resonant inelastic x-ray scattering. These experiments will be interpreted in a friendly and dynamic team environment, including
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communication skills. The ability to work in a collaborative environment with researchers from different scientific disciplines. Preferred Knowledge, Skills, and Abilities: Experience in machine learning