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and convex optimization. Prior experience in software development in machine learning systems is highly desirable. Proficient in Python and ML frameworks such as PyTorch. Independent, highly analytical
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models, and/or terrestrial biosphere models. 4. Proficiency in at least one programming language, such as MATLAB, R, or Python. 5. Ability to work effectively in an interdisciplinary and collaborative
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DAS datasets, including signal processing, quality control, feature extraction, system identification, imaging, inversion, or source characterization, is highly desirable. Proficiency in Python, C
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++, Python. Experience with Machine learning technologies (e.g., LLM, and Machine Learning) is an advantage Experience with Hardware, e.g., FPGA acceleration, is an advantage. Excellent communication skills
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signal processing, imaging, inversion, or source characterization, is highly desirable. Proficiency in Python, C++, or Julia, with strong numerical modeling, data analysis, and reproducible code
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Python, C++, or Julia, with strong signal processing, numerical modeling, and data analysis skills; experience with Git-based workflows and AI/ML for science is a plus. Hands-on experience in structural
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Publication track record is an advantage Proficiency in basics of programming languages such as ROS and Python Excellent communication skills, written and verbal – able to communicate complex concepts clearly
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programming, distributionally robust optimization, optimal transport, or reinforcement learning is highly desirable; • Programming skills in Python are desirable, especially experience with numerical
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university; Excellent programming skills, such as Python, C++, Java, Julia, or other competent languages; A good record of publications in reputable peer-reviewed journals or conferences in maritime transport
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related field). Decent programming skills, especially in Python or JAX. Familiarity with finance theory (asset pricing, derivative pricing, risk management etc.). Familiarity with machine learning or deep