Zofia Wilk

• Led the research project ”Uncertainty Quantification and Validation of Neural Network Models of Complex Physics”, focusing on assessing the reliability of machine learning models applied to materials discovery

• Run drop-in sessions for students seeking career, job application, CV and Cover Letter support. • Provided information for students in a busy and fast-paced environment. • Engaged with the evaluation and continuous quality improvement of frontline services. • Promoted the Careers Service to students as a brand ambassador.

• Generated ideas for, and contributed to the planning of series of social events targeted towards younger mature students • Actively engaged with network members online and in person to ensure an inclusive experience • Represented the University and Leeds University Union (LUU) in a professional and effective manner • Worked collaboratively, as a part of a team of Engagement Co-Ordinators and Project Leads, to meet teams objectives

• Worked within the Athena Trade and Risk Services Team using Scrum framework, participated in daily stand-ups, sprint planning and retrospective meetings, contributing to development and enhancement of Athena applications. • Leveraged knowledge in Python, HTML, Pandas, Object Oriented Programming, Unit Testing, Test Driven Development

• Key member of the 2023 Individual Research Program at the Korea Advanced Institute of Science and Technology (KAIST) within the Neuro-Machine Intelligence Laboratory led by Principal Investigator Singho Jo. • Advanced the development of the “Intelligent Fingerprint Recognition” project using Deep Siamese and U-Net Neural Networks, achieving a 97.83% accuracy in identifying distorted or damaged fingerprints. • Presented results to the NMAIL research community and discussed further ways to improve the model’s efficiency. • Leveraged knowledge in Python, PyTorch, Machine Learning, Deep Learning, Computer Vision, Scientific Writing • Developed a Machine Learning model using Deep Siamese Neural Network to recognise distorted or damaged fingerprints.

Part of Spring into Tech Insight programme. • Participated in 2023 Code for Good Hackathon • Developed programming, agility, UX/UI, Git skills during workshops • Workshadowed people from Software Engineering and Software Architecture • Attended speeches about the company and its lines of business. • Received a return offer for a summer internship

Women in Technology • Received a return offer for a summer internship

Part of Spring Insight Programme in Global Technology Division • Participated in discussion panels, workshops and keynote speeches about the Bank of America • Participated in Spotlight Sessions about Global Technology Division • Completed Global Markets and M&A Simulation on AmplifyMe • Received a return offer for a summer internship

Student Ambassador is a face and the voice of the University of Manchester. We work supporting prospective students, their families, and current students with short and long-term initiatives and events by providing support, encouragement, and advice. It is a dynamic role that involves administrative tasks, supporting and supervising students, and ensuring events are delivered effectively.

Advanced Mathematics and Statistics PASS Leader at the University of Manchester. •Organising and leading group meetings and activities. •Supporting other students with their studies.

Machine Learning track Key modules: Probabilistic Machine Learning, Deep Learning And Structured Data, Computational Statistics, Reinforcement Learning and Decision Making, Geometric Deep Learning, Speech Recognition, Advanced Machine Learning

Key modules: Machine Learning approaches, Computing, Linear Algebra, Probability & Statistics, Statistical Methods, Multivariable Calculus, Molecular Simulation, Advanced Quantum Physics, Logic, Experimental Physics Dissertation topic: What are Machines Learning about physics?