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Max Planck Institute for Radio Astronomy, Bonn | Bonn, Nordrhein Westfalen | Germany | about 1 month ago
, and the drivers of star formation and feedback across all environments and scales. We are looking for researchers with scientific interests, qualification and skills matching these aims. We particularly
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particular through (sub)mm/radio observations to connect the baryon cycle, the physics and chemistry of the interstellar medium, and the drivers of star formation across all environments and scales. We
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of cell bandgap, and spectral selectivity achieved by a photonic component, taking into account the thermal equilibrium of the cell with its environment. This approach will notably lead to the specification
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on topics including molecular clouds and star formation. Candidates with experience in machine-learning and magnetic field observation/simulation are particularly welcome to apply. Experiences with (sub-)mm
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of protoplanetary disks, and Star and Planet Formation will be offered. The postdoctoral researcher will join project ”Dust2Planets” at IPAG (From Dust to Planets: A Novel Approach to Constrain Dust Growth and the
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Leiden Observatory invites applications for a postdoctoral position to join the group of Aline Vidotto, whose research is centred around star-exoplanet connections, ranging from stellar outflows
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on a working 1D proof-of-concept. Then, the new numerical code will be applied to construct models for atmospheres and stellar winds in the cool star regime. For this, experience with stellar magnetic
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team at IJCLab, Orsay. He/she will work on the ab-initio description of asymmetric nuclear matter as it exists in neutron-star cores. The core of neutron stars is thought to consist of homogeneous matter
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performance indicators for multi-objective evolutionary algorithms. We are looking for a promising young researcher, who has the PhD completed before the contract stars. PhD degree in mathematics
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of Exeter Medical School. STARS is a collaboration with the Centre for Simulation, Analytics and Modelling (CSAM ), University of Exeter Business School; Somerset NHS Foundation Trust ; Health Data Research