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Computational biologist with extensive experience in multi-omics analysis to investigate complex diseases, including Alzheimer’s disease and colorectal, lung, and skin cancers. At Columbia University, leading glycoproteomic studies to uncover the role of glycosylation in neurodegeneration using LC-MS/MS data and advanced methods such as QTL mapping, TWAS, and colocalization. Skilled in machine learning and mathematical modeling for studying drug resistance and therapeutic response. Bringing expertise in statistical genetics, systems biology, and molecular network analysis to uncover mechanisms underlying complex diseases.

 A Mathematics student with strong quantitative and analytical skills, motivated by curiosity and logical reasoning. Eager to apply mathematical training to decision-making, proof based logic, and real-world problem solving. Excited to learn trading strategies while engaged in learning and collaborating within challenging environments. 

MPhys Physics student (predicted First Class Honours) with a strong interest in computational particle physics and simulation-based research. Experienced in developing and analysing numerical models of complex physical systems, with particular focus on stability, performance, and physical accuracy. Motivated to apply mathematical and programming skills within high-energy physics environments where computational efficiency and rigorous modelling are essential.

Applied Mathematics and German Studies student with strong training in analysis, numerical methods, and stochastic processes. Research experience includes studying the dual formulation of a Sinkhorn-type optimal transport algorithm. Internship work in Berlin focused on data-driven modeling, interpretability, and KPI-based analytics for organizational systems. Interested in mathematically grounded machine learning and rigorous data-science research.

Ronald Mbuthia

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Bachelor of Science - Mathematics And Computer Science

Master of Science - Applied Mathematics

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