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. Processing and analysis of satellite observations related to air quality and greenhouse gases. Scientific programming in Python, R, Fortran, MATLAB, or similar languages. Duties and
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of: Active learning, Bayesian optimization Reinforcement learning or decision-making systems Experience with: Python ecosystem (PyTorch, Scikit-learn) Data pipelines and scientific data handling
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++, Python, and JavaScript. Expertise in firmware development and optimization for microcontrollers and embedded systems. Knowledge of IoT communication protocols (MQTT, CoAP, LoRaWAN, Zigbee, BLE, Wi
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experience. Knowledge of process mineralogy, froth flotation through past research, coursework, or job experience. Proficiency in programming (Python, Julia) (provide evidence with specific examples
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, STRING). Proficiency in Python , R , and Unix/Linux-based environments for high-performance data analysis. Knowledge of biological network inference , causal modeling , and graph-based AI approaches
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., TensorFlow, PyTorch, Scikit-learn). Hands-on expertise in programming languages such as Python, R, or MATLAB. Solid understanding of battery systems, electrochemical processes, or energy management
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conferences (e.g., NeurIPS, ICML, ACL, EMNLP, etc.). Proficiency in programming languages such as Python, and experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth
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Multiphysics. Solid understanding of process control strategies, including model predictive control (MPC), nonlinear control, and optimal control theory. Proficiency in programming languages (Python, MATLAB
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. Criteria of the candidate: PhD degree in Computer Science or Applied Mathematics Strong publication track record in relevant research areas Proficiency in Python programming Excellent written and verbal
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learning techniques and statistical modeling. Strong programming skills in languages like Python or R. Professional experience in the application of Machine Learning algorithms in the mapping and