Curriculum Vitae
Experience, education, and skills.
Experience
Senior Applied Research Scientist
InstaDeep, London
Sep 2024 - Present
Leading applied research at the interface of multimodal (ML/DL) modelling, computational biology, and pharmaceutical R&D.
Computational Biologist
InstaDeep, London
Jun 2023 - Oct 2024
Delivered R&D projects involving medical imaging, multi-omics integration, and large language models for drug-development applications. Combined ML engineering with biological domain expertise.
Postdoctoral Research Associate
University of Cambridge - Sainsbury Laboratory (SLCU)
Dec 2021 - Jun 2023
Continued quantitative and machine-learning-driven research on high-throughput biological data at SLCU.
PhD Candidate
University of Cambridge - Sainsbury Laboratory (SLCU)
Oct 2017 - Dec 2021
Focused on quantitative, computational, and machine-learning-driven approaches to high-throughput biological data. Developed analytical tools for 3D confocal image segmentation and feature extraction; built predictive models for large datasets; and implemented finite-element simulations of deformable viscoelastic tissues. Lectured on course elements in systems biology.
Graduate Student Researcher
University of Cambridge - Sainsbury Laboratory (SLCU) (SLCU)
Jun 2017 - Aug 2017
Integrated 3D microscopy datasets with computer-vision pipelines and mathematical models of complex gene regulatory networks. Developed quantitative methods for extracting single-cell dynamics from in vivo confocal timelapses and built the extractoR data-analysis toolkit.
Research Assistant
University of Cambridge - Sainsbury Laboratory (SLCU)
Aug 2016 - Sep 2016
Worked under Professor Henrik Jönsson on computational models of stochastic spatial patterning of CLAVATA3 in the Arabidopsis thaliana shoot apical meristem. Implemented spatially balanced numerical solvers for diffusive systems and analysed noise propagation within the CLV3-WUS feedback loop.
Supplemental Instructor
Lund University
Aug 2015 - Jul 2016
Delivered instruction to groups of up to 30 students in Analytical Mechanics, Quantum Physics, and Particle Physics across Swedish and international programmes.
Research Assistant
Lund University
Jun 2015 - Aug 2015
Conducted research under Dr Carl Troein on crossover strategies for sequence alignment in genetic algorithms with variable-length genomes, applied to parameter optimisation of a gene regulatory network model of the Arabidopsis thaliana circadian clock.
Education
Ph.D., Applied Mathematics and Theoretical Physics
University of Cambridge
2017 - 2021
Thesis: Integrative high-throughput analyses of aerial morphodynamics in plants
M.Phil., Computational Biology
University of Cambridge
2016 - 2017
Grade: 1.1, with distinction. Thesis: In vivo single cell dynamics of the shoot stem cell niche in Arabidopsis thaliana
B.Sc., Theoretical Physics
Lund University
2013 - 2016
Grade: 1.1, with distinction. Thesis: Linking the dynamics of genetic algorithms to the encoding of information
Theoretical Philosophy
Lund University
2012 - 2013
Engineering Physics / Computer Science
Faculty of Engineering, Lund University
2012 - 2013
Economics
Lund University
2011 - 2012
Skills
Areas of expertise developed across research and industry roles.
Machine learning & deep learning
Transformer-based models, predictive modelling, and multimodal ML for biological and pharmaceutical applications.
Computational biology
Multi-omics integration, gene regulatory network modelling, and quantitative analysis of high-throughput biological data.
Medical & biological imaging
3D confocal segmentation, feature extraction, and computer-vision pipelines for in vivo timelapse microscopy.
Mathematical modelling
Finite-element simulation of viscoelastic tissues, stochastic numerical methods, and differential equation-based systems.
Python & C++
Development of analysis toolkits, HPC workflows, and production ML pipelines.
High-performance computing
Cluster administration, scalable data processing, and optimisation for large-scale scientific workloads.