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- Universitat Autònoma de Barcelona
- Universitat Pompeu Fabra - Department / School of Engineering
- Centre for Genomic Regulation
- Centro Nacional de Investigación Sobre la Evolución Humana, CENIEH
- FUNDACIO INSTITUT D'INVESTIGACIO EN CIENCIES DE LA SALUT GERMANS TRIAS I PUJOL
- Fundació Hospital Universitari Vall d'Hebron- Institut de recerca
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- Institut d'Investigacio Biomedica de Bellvitge (IDIBELL)
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- Universitat de Barcelona
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different sources, organize and analyze them using appropriate statistical or computer tools. - Attendance at meetings of the European Consortium, management and preparation of documents. - Collaboration in
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representative samples of citizens of four European countries within the interdisciplinary project (N=6,000 total). The successful applicant will conduct statistical research based on these data (a) analyzing how
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) or other related discipline 2. Statistical skills (R and/or Python) 3. English – C1 4. Spanish and/or Catalan and/or Basque and/or another language – B2 (desired) 5. Previous design and/or analysis
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/Qualifications Expertise in advanced statistical techniques, particularly in spatial modeling. Knowledge of spatial ecology and experience in modelling species’ habitats. Strong foundation in statistics
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. SKILLS Experience in implementing or conducting research in LMIC Experience in processing and managing of complex and large datasets, as well as in statistical packages, preferably R and STATA Motivated
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technologies (e.g., remote sensing, UAVs, multispectral imaging). Develop and implement statistical models and machine learning techniques to quantify ecosystem services provided by legumes. Contribute
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screens, statistical genetics, and the integration of genetic and regulatory data. This multidisciplinary approach gives us unique opportunities to engage in collaborative projects that combine experimental
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interventions; • Excellent methodological skills in social science research design, with particular emphasis on at least one of these: (i) advanced statistical modelling, (ii) computational methodologies (e.g
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. •Experience with large-scale datasets and advanced statistical methods is beneficial, but not mandatory.•Excellent level of spoken and written English.•Work-permit for Spain, and willingness to relocate
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(statistical or machine learning-based) of agents for Cloud and Edge environments capable of managing and explaining the behavior of SLOs. Integrate business models into the Computing Continuum framework