Employment

Business Analyst at Accelex October 2022 - August 2023
  • Performed data analytics in Excel & PowerBI
  • Wrote queries in SQL for APIs in SaaS product
  • Co-designed ETL pipeline based in Databricks

Education

University College London October 2023 - October 2026
Department of Chemistry
PhD in data-driven discovery of ferroelectric photovoltaics

University College London September 2021 - September 2022
Department of Chemistry
MSc Molecular and Materials Modelling: Distinction (83; highest mark in computational cohort)

University of Cambridge October 2017 - June 2021
Department of Chemistry
M.Sci. in Natural Sciences: II.i (66)
BA in Natural Sciences: I (74; 19th out of 101)

Camden School for Girls Sixth Form September 2015 - August 2017
A*s in A-level Maths, Further Maths, Chemistry, Physics; As in AS-level History, French
Highest grades in a year of ~300 students

William Ellis School September 2010 - August 2015
A in A-level Maths and A* in GCSE maths through self-study, both two years early
10 A*s, 1A at GCSE including French, German, History, Music, and Computer Science
Joint-highest grades in a year of ~125 students

Skills

Computational chemistry tools
  • Solid-state DFT with VASP
  • High-throughput DFT with Atomate2
  • Python packages: ASE, Pymatgen
  • Interatomic potentials with GULP
Technical experience & skills
  • Extensive experience using data analysis and ML packages (PyTorch & scikit-learn) in Python
  • HPC & BASH in Linux environment
  • Containerisation using Docker
  • Full MS Office suite
  • Creating dashboards using PowerBI as Business Analyst
  • Writing SQL queries for APIs as Business Analyst
  • Self publishing and collaboration on code using Git/hub
  • Certificates from DataCamp: Data Scientist, ML Engineer, ML Scientist (all in Python)
  • Languages: French & Italian (intermediate), Brazilian Portuguese (beginner)

Teaching

University teaching
  • 2 years as Maths Fundamentals Lead for 1st year Engineering students
  • 3 years as Demonstrator in various Computational Chemistry labs
  • 2 years as Maths Tutorial Assistant for 2nd year Engineering students
  • Training to be an Associate Fellow of the AdvanceHE (AFHEA)
Supervisee projects
  • MSc project "Dimensionality-optimised Learning of Optical Absorption Spectra" (2026)
  • MSc project "Searching for Black Swans in Materials Chemistry" (2025)
  • MSc project "Optimisation of Similarity Learning for the Discovery of Candidate Photovoltaics" (2025)
  • Undergraduate summer project "Correlating Fused Gromov-Wasserstein Distances to Photovoltaic Efficiency" (2025)