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models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly
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environments for statistical analysis (e.g., MATLAB, R, or Stata); · Creating and managing very large datasets; · Machine learning skills. Basic Qualifications A Ph.D. in any business discipline
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analysis (especially R, Stata, Julia, MATLAB, or Python) An enthusiasm for empirical research and an interest in pursuing a PhD in economics or related fields (e.g., public policy) An ability to work
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statistical packages, especially R and SPSS Good statistical knowledge and skills Good IT skills (i.e., Microsoft Office®) Strong ability to work within a multidisciplinary team Strong interpersonal, written
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Pharmaceutical Sciences or Biotechnology areas or enrollment/attendance of a non-degree course taught by a higher education institution in conjunction with an R&D unit; - Proven competences in the production and
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to the Sustainable Built Environment (SBE). The SBE team focuses on building energy modelling and simulation, decarbonization strategies for the built environment and R&D of green building technologies such as HVAC
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this position and how you learned about it The start and end dates during which you would be available to fill this position Your familiarity with programming languages (e.g. Stata, Python, R) Your prior
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call for application is open for 1 (one) Research Grant within the scope of the R&D institution University Research Center in Psychology – CUIP, Autonomous University of Lisbon (UAL), project reference
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taught by a higher education institution in conjunction with an R&D unit in Sustainable Chemistry or related areas. Experience in characterization of innovative and emerging ingredients. In case the Master
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enrolled and/or attending a non-degree course taught by a higher education institution in collaboration with an R&D unit. Proven experience, evidenced by scientific/academic publications and/or conference