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creation of a TxHC‑wide value–risk prioritization map to guide conservation investments. Design, administer, and analyze a landowner survey grounded in Protection Motivation Theory and participatory GIS
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of the most recent econometric methods to study the evolution of wealth accumulation from incomplete tax data. The applicant needs to have advanced programming skills in Stata, R and Python
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is highly desirable. A strong record of research publications is preferred. SKILLS: Strong programming skills (e.g., Python, C/C++, CUDA or similar); Background in algorithms for physical design
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(e.g. fuel cells, batteries, heterogeneous catalysts, interfaces) Proficiency in high-level programming languages, e.g. Python Previous supervision of graduate students, as well as laboratory
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: Proficient in Python. Machine Learning: Strong experience with frameworks like TensorFlow, Keras, or PyTorch. Preferred Skills: Experience with Explainable AI (e.g., SHAP, Integrated Gradients
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concepts, and 2) to enjoy finding new solutions in the face of new and unforeseen difficulties. The ideal candidate has very good 1) python programming skills, 2) understanding of the mathematical
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initiative proven through international publications in peer-reviewed media Didactic skills / experience in e-learning IT skills (e.g. Office, databases, GIS), excellent archaeological excavation and technical
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the framework of the OCP Sulfur 360° initiative. The successful candidate will contribute to a national-scale assessment of biogenic sulfur potential in Moroccan sedimentary basins. His work will combine GIS
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application in the life sciences, preferably in microbial genomics. Strong programming skills in Python or an equivalent language. Strong communication skills and experience in working in a team. The following
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. Required PhD in Computer Science / AI / Machine Learning Strong publication record in AI, ML systems, or related areas Strong programming skills in Python, C/C++ and experience with PyTorch, TensorFlow, JAX