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the Department of Chemistry and Prof. Martin Jonikas in the Department of Molectular Biology. Applicants should have experience with dual-comb spectroscopy and the acquisition and processing of associated signals
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Laboratory's activities cover a wide range of fields, from statistical physics to hydrodynamic turbulence, including mathematical physics and signal processing, as well as soft and condensed matter
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 3 hours ago
The candidate should have demonstrated experience studying asteroid or other small body populations, including thermal modeling of small bodies. acquiring, processing, and analyzing WISE/NEOWISE observations
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as point of contact for participating investigators and research sites. Assess and respond to protocol eligibility questions and operational inquiries. Escalate issues to PI as appropriate. Maintain
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to data from various sensors and radio signals? This is the main underlying theme to be explored within this postdoctoral position. The appointed researcher will investigate how AI embedded in physical
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if the degree is not completed) 6. Names and contact details of 1–3 references Please indicate in your cover letter your preferences concerning: - whether your wish to work under Prof. Hytönen, Prof. Korte
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ICT Services & Applications. The Signal Processing and Communications (SIGCOM) research group of SnT conducts research aimed at designing, emulating and testing new high-performance systems
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the ASTRID ProCoPe project (Collective Processes for Power Components), led by the III-V Lab, which aims to fabricate power components with diamond heat sinks, based on Gallium Nitride (GaN), and to develop
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knowledge, skills and successful experience in several of the following research areas: • Sub-Kelvin Refrigeration Concepts, operation and maintenance of sub-kelvin 3He-refrigerators and 3He-4He dilution
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Experience developing pipelines and code for gravitational-wave searches and/or parameter estimation Knowledge of advanced Bayesian methods and samplers, machine learning approaches to signal processing