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CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | 3 days ago
well as bioactivity of seafood and insects, prepared products and co-products, ii) development of food prototypes, (iii) data processing, and iv) analysis of results. The candidate will also be involved in several
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processing, analysis and interpretation of simulated data, which is proven by attaching separate papers. In accordance with the terms and conditions of PDIP-2026, for all points of the Call the applicants must
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8 Feb 2026 Job Information Organisation/Company University of Oslo Research Field Mathematics » Statistics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline
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biophoton detection experiment (measuring photon counting statistics from biological tissue). This involves setting up optical equipment, preparing samples, acquiring data, and performing statistical analysis
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laboratory’s website for more information: http://orion.bme.columbia.edu/leonglab/ . The lab is located on the medical campus of Columbia University. The minimum educational qualification is a PhD degree in a
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Knowledge, Skills, and Abilities Demonstrated experience with electrophysiology data analysis. Strong quantitative and programming skills (e.g., MATLAB, Python, R). Solid background in signal processing
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Responsibilities Responsibilities include: Leading a project in coral stem cell isolation, characterization, preservation, and propagation Develop and implement data analysis and visualization strategies, perform
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consult the additional and detailed information on Data Protection on our website: http://www.icra.cat/politica-de-privacidad Website for additional job details https://icra.cat/en/oferta-treball
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research, research groups require access to high performance data storage for data-intensive processing, visualization for data analysis, GPUs, access to cloud services and research infrastructure skills
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PhD working with Prof. Hendrik Blockeel and/or Prof. Jesse Davis on analysis of time series data. The goal is to develop algorithms for detecting anomalies, discovering “motifs” (repeating patterns