Selected work.

Current work at the Novo Nordisk Foundation Center for Protein Design on de novo β-sheet and β-sandwich architectures — new folds assembled from first principles and characterised experimentally.

Methods drawn from generative protein design, molecular modelling, sequence design, and structural prediction, with the loop closing at the bench.

PFAS — per- and polyfluoroalkyl substances — are persistent environmental contaminants with few natural biological handles. This project asks whether de novo proteins can be designed to recognise them selectively.

Targets include molecular recognition, sensing, sequestration, and eventual breakdown of fluorinated compounds, combining design in silico with experimental characterisation.

Worked with Professor Thomas Gorochowski in the Biocompute Lab to build NoRDe, a toolkit that designs RNA variants preserving secondary structure while minimising sequence similarity.

Incorporated heuristics including Hamming distance, GC content, and clustering. Validated 6 variants individually and generated a 12× array for simultaneous edits in E. coli.

Used Python, Matplotlib, and Seaborn for data analysis and computational predictions.

As team leader (2021–2022), I directed a 15-member interdisciplinary team engineering a denitrification pathway in E. coli. Coordinated molecular cloning, plasmid verification, and lab experiments, and modelled pathway output in MATLAB.

Designed and characterised a novel sequence submitted to the Registry of Standard Biological Parts, and 3D-modelled a biofilter for nitrate catabolism. Secured roughly €20,000 in project funding.

As wet lab advisor (2023–2024), I guided student teams through molecular cloning and multi-gene plasmid assembly, and used AlphaFold2 and PyMOL to predict protein structures and inform design decisions.

Analyzed enzyme kinetics in Python and MATLAB, and managed roughly €25,000 in project funding across two seasons. Work featured in ERT, Vice, and RThess.