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from the Department of Civil and Environmental Engineering. This position is part of an exciting research programme aimed at advancing the multi-robotic wire-arc directed energy deposition technology and
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planet”. For section 2.2 Geophysical Imaging (department “Geophysics”), we are looking for a: Reference Number 10887 Recent advances in quantum technology have made operational quantum gravimeters possible
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for imaging Apply for this job See advertisement About the position Position as PhD Research Fellow in machine learning available at Department for Informatics with the research group Digital Signal Processing
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Science Institute and the Nano and Micro scale research Centre. You should have or working towards a PhD in Engineering, optics or physics. Knowledge or experience on the use of Spectra Physics tsunami
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 2 months ago
inhibitors or CRISPR technology, accessing proteomic results from immunospheroid cultures. The work to be carried out by the PhD fellow includes the curation and management of a blinded clinical database
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the academic promotions process. About You Completed PhD (or equivalent experience) in Mechanical Engineering, with an established profile and over 10 years of professional experience in mechanical or opto
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they are developing Required Qualifications* PhD Degree in Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, or a related field Familiarity with (biomedical) signal processing Experience
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therapies and clinical trials. Your responsibilities will include: processing FASTQ and BAM/CRAM files, and producing variant call files, generating input data for AI tools and implementing secure
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17 Nov 2025 Job Information Organisation/Company Universidade de Coimbra Research Field Economics » Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Portugal
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the group's research on developing novel machine learning/computer vision methodology. The focus of this project will be on the development of deep learning methodology for spatio-temporal medical image