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, R’ or Python programming, Co-supervise PhD and undergraduate students. Be willing to be involved in other research activities different than spectroscopy, such as soil phosphorus, agronomy
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field, expertise in AI/ML (e.g., PyTorch, TensorFlow, Python), interest in materials applications, and a strong publication record. The position is for two years, with the possibility of renewal, subject
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machine learning and statistics; experience with Gaussian process regression and/or probabilistic regression. Experience with normative modelling is an advantage. Proficiency in Python (and ideally C/C
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background in machine learning, predictive modeling, or applied AI Proficiency in Python and/or R; experience with libraries like scikit-learn, XGBoost, TensorFlow. -Experience working with real-world datasets
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, organization of scientific workshops, and attendance at conferences. Key qualifications include a PhD in a relevant field, expertise in AI/ML (e.g., PyTorch, TensorFlow, Python), interest in materials
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Python, MATLAB, or C++. Experience with machine learning techniques, CAD, computational modeling, 3D printing, motion capture, and/or material testing. Proficiency in programming languages commonly used in
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proficiency in Python and/or R; familiarity with working in a Linux/Unix environment; fluency in English (both written and spoken); excellent communication and teamwork skills in an interdisciplinary
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, Python, Matlab, and C++) would be advantageous. The appointee will work with a research team to study the methodologies for estimating population immunity against infectious diseases, to analyse large and
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programming in R, Python, and mathematics/statistics. The main duties involved in a post-doctoral position is to conduct research. Teaching may also be included, but up to no more than 20% of working hours
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pipelines in Python and R. Perform experiments in cell culture and animal models to validate the findings. Coordinate the collaboration between the chronobiology lab (led by Dr. Paul Petrus) and the