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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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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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/ ROS 2 for real-robot software integration. Proficiency in Python and C++, with good software engineering practices (version control, testing, maintainable code). Familiarity with robotics simulation
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Responsibilities Work closely with the PI, Co-PI, and research team to ensure timely completion of all project deliverables. Implement and enhance GeoTOPSIS/VectorMCDA algorithms within QGIS using Python
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, diesel generators, and other sources. Implement predictive, rule-based, or optimisation-based control strategies using MATLAB/Simulink, Python, or embedded software tools. Integrate controller logic with
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Python programming and relevant libraries (e.g., OpenCV, NumPy, scikit-learn, Pandas, Matplotlib) Experience with dataset preparation, model training, and performance evaluation Candidates with strong
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. Knowledge of visual 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