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and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly for developing Windows desktop application software incorporating deep learning models 2. Hold at
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support systems. To be successful for this position, you’ll have: Demonstrated experience in the application of LLM. Demonstrated experience in programming in Python. Ability to learn new technology and new
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: · MATLAB · Python · ROS · Computer vision and/or YOLO · Pytorch and/or Tensor Flow · LiDAR · GIS · GNSS receivers Minimum Qualifications: Doctoral degree in Mechanical Engineering, Electrical Engineering, or
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maintains local and national data repositories. Generates routine reports, statistical summaries, and figures using SAS, R, or Python. Optional: contributes to wet lab tasks (e.g., tissue sectioning, IHC
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electrophysiology: Proficiency in whole-cell patch clamp recording, acute slice preparation, and/or cell culture electrophysiology, along with related data analysis methods using tools such as MATLAB or Python
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community. Required Skills and Qualifications: Minimum PhD in computer science/ engineering or related fields. Proficiency in Python is a must. Experience with other programming languages such as Java, C/C
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in machine learning, AI and programming skills, e.g. Python basic knowledge of materials science / materials engineering Leibniz-IWT is a certified family-friendly research institute and actively
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-academic venues. • Experience with programming (primarily Python) and machine learning libraries. • Curiosity and passion to explore new concepts, methods and technologies, and capability
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-academic venues. • Experience with programming (primarily Python) and machine learning libraries. • Curiosity and passion to explore new concepts, methods and technologies, and capability
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to program in Python; conduct appropriate statistical analysis of experimental data. Strong oral and written communication skills. Ability to mentor undergraduate and graduate students. Ability to travel