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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 2 months ago
Stage Researcher (R1) Positions PhD Positions Country Portugal Application Deadline 15 Oct 2025 - 00:00 (Europe/Lisbon) Type of Contract Other Type of Contract Extra Information Research fellowship Job
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical technology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess
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6 Nov 2025 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Country Portugal
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical techn ology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess
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engineering, computer science, physics or related fields). A PhD* (or equivalent research experience) in a relevant subject (only for Research Fellow position). Candidates with a non-healthcare degree are
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related to staff position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Job description: GFZ is Germany's national centre for solid Earth research
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-disciplinary team of researchers, including bioinformaticians, pathologists, oncologists, and computer scientists, and conduct original research on computational pathology. Digital pathology images contain rich
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 5 hours ago
PhD in seismology, geophysics, computer/data science, or planetary science. You will have demonstrated expertise in global seismology, particularly relating to the Earth’s core, core–mantle boundary
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, imaging approaches and/or bioinformatics. Postdoctoral Fellow – Banerjee Lab – 00399 Our lab is interested in how the brain accomplishes the ongoing transformation from sensation to action during natural
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical techn ology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess