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in dynamical systems modeling (ODEs) and machine learning and very strong programming skills (Java, Python). A background in evolutionary genomics research is a strong plus, as is previous experience
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statistical and geospatial analyses (e.g., using ArcGIS, SPSS, Stata, Python, R). Conduct cross-city comparative research Map and analyse the geographical distribution of eviction patterns within and across
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core network protocols Proficiency in multiple programming languages including bash scripting, MATLAB, C/C++ and Python. Other simulation languages such as JULIA are pluses Working knowledge
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, Vehicular Communications Experience in system modeling and simulation of communication systems Strong programming skills in MATLAB are required; experience with Python, C/C++, or GPU-based computing is an
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, including hands-on implementation Strong understanding of machine learning models and their development Strong analytical, problem solver, and programming skills for Python and Matlab are preferred Experience
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languages such as Python A collaborative team player with a desire to make a personal impact within our interdisciplinary research group and our broader economy and society The commitment to participate in
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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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, Stata, Python, R). Conduct cross-city comparative research Map and analyse the geographical distribution of eviction patterns within and across cities; Examine similarities and differences in urban
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programming or scripting skills (e.g., Python, MATLAB, Bash) are a plus Prior experience in amyloid biology, protein aggregation, or disease-related structural research are an advantage. Ability
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models), programming skills in Python or a similar programming language (experience with PyTorch or another machine learning library is required), at least a basic expertise in user experience (UX) and