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will bridge rigorous theoretical work with hands-on offloading algorithm design and development. The core responsibility is to build and validate these offloading strategies, complete with Python
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materials characterization (e.g., SEM, XRD, FTIR, mechanical testing). Proficiency in data analysis tools (Python, MATLAB, JMP) and technical documentation. Strong analytical skills and attention to detail
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in programming, preferably in Python, MATLAB, C/C++, or similar environments. Experience in experimental work, data collection, and system troubleshooting is desirable. Familiarity with ultrasound
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in algorithm development using Python and ML frameworks such as PyTorch or TensorFlow. Key Competencies Work independently, as well as within a team, to ensure proper operation and maintenance
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Python and deep learning frameworks (e.g., PyTorch) Interest in applied, industry-collaborative research Where to apply Website https://www.timeshighereducation.com/unijobs/listing/413018/research-fellow
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background in power systems, energy modelling, or grid optimisation Proficiency in GUI development (e.g. using Python Dash, Tkinter, or web-based frameworks) Experience working with data-driven simulation and
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generation and multimodal LLM will be advantageous. Key Competencies Proficiency in programming languages (e.g., Python and C++), and familiarity with AI frameworks (e.g., PyTorch). Self-directed learner who
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Learning Video Understanding Multimodal AI Excellent programming skills in Python. Hands-on experience with: PyTorch Hugging Face Transformers OpenCV Experience working with deep learning models for image
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, Artificial Intelligence, Software Engineering, or a related field. Strong programming proficiency in Python and/or C++. Demonstrable experience with machine learning frameworks (e.g., PyTorch, TensorFlow
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, Google Cloud, Microsoft Azure), including containerization (Docker), orchestration (Kubernetes), serverless computing, and REST API development. Proficient in Python, with basic experience in machine