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of instrumentation scientists, applied mathematicians, and computational scientists, and building worldwide collaborations aimed at tackling the challenges posed by terabyte and petabyte-scale imaging data processing
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microscopy Experience in live super resolution imaging Oral and written skills in English language Scientific conference participation Publication record PhD Student Position 3 Required qualifications: BSc in
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equipment acquisitions and emerging imaging technologies; assisting in the preparation of funding requests for new or replacement instruments. Qualifications Required: PhD in a relevant field (e.g., molecular
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, Communication Engineering, Computer/Data Science, Mathematics, or equivalent; – knowledge in artificial intelligence, image/signal processing, remote sensing, and radar remote sensing. Where to apply Website
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Description About the position We are looking for a motivated PhD candidate to join a multidisciplinary research team working on predictive modeling of clinical outcomes after Deep Brain Stimulation (DBS) in
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applications for RGC grants, other local/overseas competitive grants and/or fellowship schemes. General Requirements Candidates should have (i) a PhD degree in imaging science or related field or an equivalent
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be evaluated for lung diseases imaging which are still challenging to diagnose and treat, despite advancements. We will carry out preclinical studies to evaluate the contribution in combination with
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21 Apr 2026 Job Information Organisation/Company Fondazione Bruno Kessler Research Field Other Researcher Profile Other Profession Positions PhD Positions Application Deadline 15 May 2026 - 23:59
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remains challenging, limiting multiscale imaging approaches in near-field holotomography. To address this, the PhD project combines machine learning, high-performance computing, and synchrotron-radiation
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at VU as well as ETH Zurich be available for medium-duration (weeks) secondments at ETH Zurich to ensure knowledge transfer Where to apply Website https://www.academictransfer.com/en/jobs/360013/phd