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Field
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relation to temperature-related health risks. Have experience in statistical and spatiotemporal analysis using R, Python, MATLAB, or similar analytical tools. Have good organizational and communication
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, Security, and AI Generation Models. Experience with deep learning frameworks such as PyTorch or TensorFlow. Proficiency in programming languages including C/C++, Python, Java, and Go. Familiarity with
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., Python/C/C++/Fortran). Experience with HPC (Linux, batch systems) and handling large simulation datasets (I/O, post-processing, analysis). Background in theoretical physics with at least basic knowledge
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programming languages, e.g. C/C++, Python. Experience with Machine learning technologies (e.g., LLM, and Machine Learning) is an advantage Experience with Hardware, e.g., FPGA acceleration, is an
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programming languages, e.g. C/C++, Python. Experience with Machine learning technologies (e.g., LLM, and Machine Learning) is an advantage Experience with Hardware, e.g., FPGA acceleration, is an
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Proficiency in GUI development (e.g. using Python Dash , Tkinter , or web-based frameworks ) Experience working with data-driven simulation and model validation in power grids (Ph.D level is mandatory
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Proficiency in programming languages (e.g., Python and C++), and familiarity with AI frameworks (e.g., PyTorch). Familiarity with multimodal AI frameworks, large language models (LLMs), or vision-language
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independently Confidence with computational biology including use of programming languages such as R, python and some familiarity with high performance computing Excellent communication and interpersonal
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-based models. • Ability to sophisticatedly use at least one programming language, e.g., Python, R Java, SQL, Julia, C# and C++. • Excellent interpersonal and communication skills. • Good
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bulk and single cell RNA-seq, ATAC-seq and CHIP-seq. · Expertise in downstream analysis and biological interpretation of bioinformatic findings · Proficiency in R/Python programming