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RESEARCH FELLOWSHIP Title: Research Fellowship - 1 position CIPSI-ID-ICDT-16400-01 A call is open for the award of one (1) Research Fellowship within the scope of the R&D project “Breaking the Cycle
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the educational project of a higher education institution, developed in association or cooperation with one or more R&D units); - Other documents considered relevant by the candidate. To ensure reading of all
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. Technical Competencies Proficiency in Python, R, or similar programming languages for data analysis and modeling. Familiarity with AI/ML model evaluation, risk metrics, or reliability analysis. Experience
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-performance computing (HPC) or cloud-based big-data pipelines. Experience with large-scale human genomic, omics, or brain imaging datasets. Strong programming skills in Python, R, or MATLAB, with emphasis
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for R&D activities carried out by students enrolled on a PhD course). or b) Non-conferring degree courses: (Research grant is intended for R&D activities carried out by masters enrolled on non-degree
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accepted. Closing Date: 21 Nov 2025 Category: Research and Teaching (R&T) Where to apply Website https://academicpositions.com/ad/university-of-nottingham/2025/research-fellow-… Requirements Research
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-dimensional data analysis. Proficiency in R or Python; experience with deep learning, causal inference, or genetic data analysis is not required but encouraged. Excellent written and verbal communication skills
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surveys; Programming/scripting knowledge suitable for processing raw data for analysis (e.g., text manipulation); One or more computational environments for statistical analysis (e.g., MATLAB, Stata, R
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 23 days ago
award a grant for the development of R&D activities by doctoral students, enrolled in doctoral programs, or by Master´s enrolled in non-academic degree courses integrated into the educational project of a
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Curricular Evaluation (with a weight of 0 - 20 points) are: - Average grade of the last academic degree obtained (85%) - R&D experience in the scientific area of the competition (10%) - Number of scientific