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following areas: Mathematical Analysis/ Numerical Analysis/ Theoretical Machine Learning Please note: Applications from candidates with degrees in other disciplines (e.g., Computer Science, Engineering) will
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positions) / a PhD (Postdoc positions) in natural sciences (i.e. Chemistry, Physics, or Materials Science) preferably with a specialization in theoretical chemistry, or applied mathematics An appropriate
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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | 3 months ago
high-impact scientific journals Essential skills and qualifications MSc and/or PhD qualifications in Chemistry, Physics, Materials Science, Computational Science, Engineering or a closely related field
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: Masters and subsequent PhD in Physics, Chemistry, Material Science or related disciplines Experience in neutron spectroscopy, e.g. INS, QENS, NSE Good knowledge of the structural characterization of matter
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molecular/condensed matter physics) and the developments on new tools in perturbation theory and in computational methods (gradient flow), including quantum computing. We look for ambitious candidates with a
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research strategy, including fundamental and applied approaches You will create, process, analyze, and interpret the research data, prepare reports, and scientific publications You will take part and present
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: completed scientific higher education degree (PhD) in the field(s) of Earth system science, physics, climate physics, geosciences, mathematics, computer science or a comparable field demonstrated experience
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: completed scientific higher education degree (PhD) in the field(s) of Earth system science, physics, climate physics, geosciences, mathematics, computer science or a comparable field demonstrated experience
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technologies to fundamental physics questions. The advertised positions will be part of the project “QS-Gauge: quantum simulation of lattice gauge theories”, funded by the Emmy Noether programme of the DFG
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energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes