Recent medical graduate with strong academic performance and a research-focused mindset, including a thesis on machine learning applications in Anesthesia (Features from Pupillary Reflex Dilation and neural networks classification of remifentanil effects, graded 18/20). Experience in multiple clinical rotations, with exposure to public health and hospital settings, demonstrating solid clinical knowledge, patient care skills and adaptability. Highly motivated, detail-oriented and eager to contribute to medical practice and resarch, combining evidence-based decision-making with technological insight. Fluent in English, with excellent communication skills and a commitment to professional growth and lifelong learning
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