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to autonomous systems is considered an asset. Proficiency in relevant programming and simulation tools, such as Python, C/C++, MATLAB/Simulink, ROS/ROS 2, Gazebo, AirSim, or equivalent platforms. Experience in
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methods is a plus Programming experience in MATLAB and/or Python Familiarity with process simulation software such as Aspen Plus or Aspen HYSYS Application and Selection: The application folder must contain
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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 understanding
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, 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. Preferred Skills
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related field. Strong track record in remote-sensing imagery and/or time-series analysis and ML/DL for spatio-temporal data. Advanced Python skills and experience with ML frameworks and geospatial tools
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advanced AI frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with bioinformatics tools and databases (e.g., Bioconductor, Galaxy, KEGG, Reactome, STRING). Proficiency in Python, R, and Unix/Linux
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or retrosynthesis (e.g., reaction templates, template-free approaches). Proficiency in Python programming and familiarity with ML frameworks such as TensorFlow, PyTorch, or JAX. Experience with cheminformatics tools
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of process control strategies, including model predictive control (MPC), nonlinear control, and optimal control theory. Proficiency in programming languages (Python, MATLAB) and experience with AI/ML
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. Strong programming skills in languages like Python or R. Professional experience in the application of Machine Learning algorithms in the mapping and correction of spatial data. Professional experience in