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of Cryptography, Computer security or any related field. Strong publication record in high impact conferences / journals. Very good programming skills (e.g., C, C++, Python), familiarity with Linux Proficiency in
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architecture. Programming skills in Python, ROS, TensorFlow, or MATLAB. Strong interest in applied AI and autonomous systems development. Application materials: CV, cover letter, and one recommendation letter.
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DFT for studying reaction mechanisms and materials. Demonstrated programming skills (Python, Fortran, C++). Proven track record of publishing scientific papers in peer-reviewed journals. Skills and
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for spatio-temporal data. Advanced Python skills and experience with ML frameworks and geospatial tools (e.g., PyTorch/TensorFlow, rasterio/GDAL). Ability to work independently and produce reproducible
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: PhD in solar energy, electrical engineering, or environmental sciences. Proficiency in PV systems, instrumentation, and performance measurement. Experience in processing environmental data (Python, R
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of field campaigns, data collection and lab work, Spectral data analysis, data processing, and model development, ‘R’, Python programming / package development, Co-supervise PhD and undergraduate students
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Python programming and familiarity with ML frameworks such as TensorFlow, PyTorch, or JAX. Experience with cheminformatics tools (e.g., RDKit, Open Babel) and chemical reaction databases (e.g., Reaxys
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machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on expertise in programming languages such as Python, R, or MATLAB. Solid understanding of battery systems, electrochemical
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sequencing (NGS) and omics data analysis. Knowledge of microbial ecology, dysbiosis, and host-microbiome interactions. Familiarity with cell culture techniques. R, Python, or other data science tools
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language processing. Experience with transformer-based architectures (e.g., BERT, GPT) is highly desirable. Proficiency in Python and relevant machine learning libraries (e.g., TensorFlow, PyTorch). Experience with