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to emerging or re-emerging diseases. Proficiency in programming languages such as Python, R, SQL, or similar tools for data analysis and model development. Experience in working with large and complex datasets
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transferability. Data pipelines for structured and unstructured data (images, text, social media, retail data) will be designed and validated on real-world case studies. Where to apply Website https
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the development of novel mathematical and computational approaches for advanced relational data analysis. Where to apply Website https://pica.cineca.it/unimc/20-br-071/ Requirements Research FieldTechnology
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flow cytometry. Experience and ability to work with in vivo models including mice. Experience with coding including R or Python. Experience with supervision of students and junior staff. Classified Title
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of relevant job experience Familiarity with Programming (Python, R, etc) Background in psychology, anthropology Excellent communication and interpersonal skills Proficient in Microsoft software (Word, Excel
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in a relevant field (e.g., computational linguistics, digital humanities) Excellent programming skills, with extensive experience in Python Extensive experience with recent Python-based machine
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experiments using high-level programming languages (e.g., Python, MATLAB, R, or Julia). Curate and integrate experimental data to calibrate and validate models, including parameter estimation and uncertainty
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practice (e.g., Python/MATLAB/C++ and/or established modelling platforms). Familiarity with asymptotic and multiscale mathematical analysis methods to ground proof numerical simulations Strong communication
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acquisition, calibration, uncertainty/rigour and noise control). Strong signal processing skills (e.g., using Python and/or MATLAB). Ability to work effectively in an interdisciplinary team and communicate
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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