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models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly
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vision and deep learning concepts, including object detection and image-based classification, with hands-on experience using Python and at least one deep learning framework (e.g., PyTorch or TensorFlow
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Software: Extensive experience with the Robot Operating System (ROS/ROS 2). Programming: High proficiency in C++ and Python for real-time robotic applications. Simulation: Experience with realistic
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algorithms for dynamic master selection, coordinating BESS, PV, diesel generators, and other sources. Implement predictive, rule-based, or optimisation-based control strategies using MATLAB/Simulink, Python
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(Kubernetes), serverless computing, and REST API development. Proficient in Python, with basic experience in machine learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP
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maintenance of equipment. Job Requirements Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field. Strong programming proficiency in Python and/or C
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, Python, or equivalent will be an advantage. Prior experience in laboratory testing, data analysis, or industry-related engineering projects will be an advantage. Key Competencies Ability to build and
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Python or other equivalent programming languages. Strong foundation in data analytics and data-driven modelling. Able to build and maintain strong working relationships with people within and external
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-on experience using Python and at least one deep learning framework (e.g., PyTorch or TensorFlow). Basic experience handling and processing sensor data (e.g., camera, thermal, LiDAR, RADAR, or similar perception
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. Proficiency in data analysis software (e.g., R, MATLAB, SPSS, Primer, Python). Experience with analytical techniques such as ANOVA, PCA, Regression, and Multidimensional Scaling (MDS). Experience in ecosystem