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-of-principle FFS measurements on various test samples Support the supervision of a PhD student ESSENTIAL REQUIREMENTS A PhD in physics, biophysics, engineering or a related discipline Documented experience in
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/Offerte_di_lavoro_A_Researcher_in_the_Field_of_Deep… Requirements Research FieldPhysicsEducation LevelPhD or equivalent Skills/Qualifications Job requirements The ideal candidate should have: PhD degree, preferably in the field of Climate Physics
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from different disciplines Contribute to scientific publications and dissemination of results ESSENTIAL REQUIREMENTS PhD in Physics, Photonics, Condensed Matter, or a closely related discipline Proven
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to perform correlative operando measurements Essential requirements PhD in Material Science, Chemistry or Physics or equivalent degree Hands-on experience in electrochemistry Hands-on experience in Raman and
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are to date the closest avenues to investigate, but other topics are not excluded, such as, e.g., physics and weather forecast. Supervise the research activities of PhD students. Publications on major
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experimentation with our partner surgeons (both in the lab and in the OR). The position requires physical presence in the lab at IIT in Genova, Italy. Remote work is not possible. Your main responsibilities will be
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application contains the following attachments (in pdf format): detailed CV; cover letter indicating why the candidate is suitable for this position. Selection process Selection process and assessment criteria
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(UTC) Country Italy Type of Contract Other Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a
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Profile Recognised Researcher (R2) Positions PhD Positions Application Deadline 31 Mar 2026 - 23:00 (Europe/Rome) Country Italy Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer
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Is the Job related to staff position within a Research Infrastructure? No Offer Description Postdoctoral Researcher in Software Engineering & Robotics (MLOps for AI-Enabled Cyber-Physical Systems