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of $75,000, full benefits, and a research account of $4,000 per year. Eligibility is limited to candidates whose PhD will be conferred by August 1, 2026. Application Procedures: The following application
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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 10 days ago
of solar physics and planetary research, with around 300 employees. The interdisciplinary research focus is the investigation of the development, diversity and dynamics of planets, moons, small bodies
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perform numerical simulations. Key Requirements for Postdoc: Requires a PhD in Physics or closely related disciplines. Experience with numerical software (VASP, Quantum Espresso) and programming (e.g
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://drive.google.com/file/d/17SY2HfckkPZp8GVtRelkIxrGhikP92nN/view?usp=sharing Job Requirements REQUIRED: PhD in materials science, physics, electrical engineering, chemical engineering, or a related field by the start
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knowledge required for technological applications. Moreover, the candidate should contribute to the studies of heat capacity (Cp) in 2D van der Waals materials. Requirements: Education: PhD in Physics
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Food Protection Consortium, working with plastic packaging and recycling to evaluate contamination, regulation, and properties. Required Minimum Qualifications: PhD Preferred Qualifications: Experience
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operation process. Particularly, we seek to support architects to design more sustainable buildings through simulation-assisted performance feedback regarding initial design concepts. We will explore how AI
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“Quantifying Efficacy and risks of solar radiation management (SRM) approaches using natural analogues”. The project will use novel machine learning-based methods to determine the climate response to a range of
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, present, and report research results and publish scientific results in key peer-reviewed journals in due time. CANDIDATE PROFILE PhD degree in Physical Chemistry, Chemical Physics, or a related discipline
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We are seeking to recruit a 2-year postdoctoral researcher within Human-Computer Interaction to work on the interdisciplinary project DARES: Data Quality for Responsible AI in Energy Systems funded