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Nianzhen
17/h
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Experienced computer science background, good at python and biology. Currently studying MSc Bioinformatics at ETH

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With a strong academic foundation and hands-on experience in computer science, mathematics, and biology, I bring an interdisciplinary skill set ideally suited for both technical development and teaching roles. I am currently pursuing a Master’s degree in Computational Biology and Bioinformatics at ETH Zürich, where I’ve built on my solid undergraduate background—graduating with First Class Honours in Computer Science (AI concentration) and Applied Mathematics minor from Hong Kong Baptist University.

Throughout my academic journey, I have developed a high level of proficiency in Python, R, Java, and deep learning frameworks such as PyTorch and TensorFlow. I’ve applied these tools extensively in machine learning projects, with a particular focus on bioinformatics. For example, as a Software Development Intern at Lunaphore Technologies in Switzerland, I worked on developing machine learning algorithms for cell segmentation in immunofluorescence images. The model I trained was successfully integrated into the company’s software platform.

I also gained research experience as an assistant at Hong Kong Baptist University, where I helped develop a large language model for taxonomic classification of DNA sequences. Additionally, my bachelor’s thesis focused on clustering bacterial sequences using deep learning. These projects not only deepened my understanding of algorithm design and data analysis, but also honed my ability to communicate complex ideas—an essential skill for effective teaching.

My diverse expertise, structured working style, and enthusiasm for sharing knowledge make me a strong candidate for educational and tutoring roles.
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