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, TensorFlow) and Python ML libraries (e.g., NumPy, OpenCV, scikit-learn). Experience implementing and evaluating state-of-the-art tracking algorithms such as DeepSORT, ByteTrack, and Transformer-based
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as occlusions, crowded scenes, and object re-identification. Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow) and Python ML libraries (e.g., NumPy, OpenCV, scikit-learn). Experience
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metrics, or similar frameworks. Strong programming skills in R, Python, or similar, with the ability to write reproducible, well-documented code. Familiarity with high-performance computing (HPC
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publications, commensurate to opportunity. Demonstrated proficiency in Python, including data handling and backend development. Demonstrated experience developing applications interfacing with machine learning
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management and programming languages such as R and Python. Level B Essential Criteria: A PhD in entomology or a related discipline, with at least 3 years of postdoctoral experience. A strong track record in
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-object tracking in challenging conditions such as occlusions, crowded scenes, and object re-identification. Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow) and Python ML libraries (e.g
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systems. Demonstrated skills in programming in Python, R and sound abilities in AI and data analytics A developing reputation and track record of publications in reputed refereed journals and presenting
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, energy systems optimisation, techno-economic forecasting, or agent-based modelling proficiency in scientific programming (preferably Julia, Python, or MATLAB) competence in data analysis and probabilistic
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analytical chemistry, particularly GC-MS analysis of trace volatiles Good communication and problem-solving skills Knowledge in data analytics (python or R) is desirable Knowledge in atmospheric chemistry is
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experience working both independently and collaboratively in interdisciplinary teams. Your excellent communication skills and programming proficiency (e.g., Python, MATLAB, R) support your ability to lead or