Sam Whitby, PhD

About

Sam Whitby, PhD

Inventor and interdisciplinary scientist adept at building biosensing technologies from first principles through to working products. Proficient in computational physics with doctoral experience simulating quantum, biological and electrochemical systems. First employee at Osler Diagnostics: set up the research laboratory from scratch, helped scale the company to over 100 people, and contributed to a $30M Series A funding round.

An effective communicator with a proven record of innovation including patented biosensing technologies and highly original research concepts. Advises multiple biosensing companies through private consultancy, rapidly deploying advanced computational models to address bespoke R&D requirements.

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Experience & Education

Curriculum Vitae

Experience

2020–2025

Private Consultant · Biotechnology Startups

Provided consulting to multiple clients on proprietary biosensing methods — delivering literature reviews, scientific advice on electrochemical devices, and bespoke software, simulations and models. Clients include Osler Diagnostics, Sense-Bio (now OraSure Technologies), and the Compton Group, Oxford.

2019–2020

Senior Scientist · Osler Diagnostics

Project lead for Blood Chemistry R&D. Managed 5–10 scientists to develop quantitative electrochemical assays for proteins, ions and metabolites. Translated assays to a second-stage prototype, collaborating across electronics, microfluidics, and embedded software teams. Invented a novel method for high-throughput electronic multiplexing.

2017–2019

Scientist · Osler Diagnostics

First hired employee. Established the research laboratory and translated biosensing technology from the University of Oxford into the company. Delivered a functioning prototype point-of-care device capable of measuring multiple protein biomarkers in blood, contributing to a $30 million Series A raiser.

Education

2021–2026

PhD in Bioengineering · Imperial College London

Thesis: "Memory in Models of Molecular Assembly". Supervised by Dr Chiu Fan Lee and Dr Thomas Ouldridge. Funded by the President's Scholarship. Passed examination February 2026, examined by Prof Jon Doye and Dr Ruben Perez-Carrasco. Work presented at Physics of Emergent Behaviour IV (Harrogate, 2023), Imperial Early Career Research Symposium (2023), and Smart Condensates and Droplets Symposium (Cambridge, 2024).

2013–2017

MChem Chemistry · University of Oxford

First Class Honours (average 80%), first prize for best thesis. First on all 16 examination papers. Master's thesis: "Application of the Frozen Gaussian Approximation with Stochastic Surface Hopping to Non-adiabatic Photochemistry".

Technical Skills

Python Mathematica Fortran Claude Code Monte Carlo methods Machine learning Finite-element methods Electrochemistry Immunoassay development Biosensor design Potentiostat design Qualified phlebotomist

Research

Publications & Patents

Publications

2026

Memory in Models of Molecular Assembly

Whitby, S.

PhD Thesis — Imperial College London

View thesis ↗

2017

Application of the Frozen Gaussian Approximation with Stochastic Surface-Hopping to Nonadiabatic Photochemistry

Whitby, S.

Master's Thesis — University of Oxford

View thesis ↗

2016

Single Nanoparticle Voltammetry: Contact Modulation of the Mediated Current

Li, X., Batchelor-McAuley, C., Whitby, S. A. I., Tschulik, K., Shao, L., & Compton, R. G.

Angewandte Chemie International Edition, 55(13), 4296–4299

doi:10.1002/anie.201509017 ↗

Patents

2023

Device for detecting presence or absence of a chemical or biological target within a sample

Whitby, S.

U.S. Patent Application US 2023/0020979 A1 — Electrode functionalised with an antibody and corresponding detection method

US 2023/0020979 A1 ↗

2024

Methods for immunoassays using electrochemical measurement

Sokolov, S., Merotra, J., Psarros, K., Whitby, S., Dos Santos, A., & Bedatty Fernandes, F. C.

U.S. Patent 12,168,794

US 12,168,794 ↗

Other Work

Selected Projects

A selection of work spanning computational science and music technology.

Automated Arranging for Live Ensembles

Divisi

Divisi arranges any score, MIDI recording or leadsheet into playable string-quartet or brass-band parts, sent to each musician's phone or iPad as a QR-coded part. A machine-learned model, trained on hundreds of professionally engraved quartet scores, choses who plays each note and checks its own output against that same corpus for register, doubling, and playability.

The app is currently in active development and testing, having received interest from wedding bands and quartets.

Python · FastAPI · PyTorch · music21

Formal Verification for Computational Physics

Detailed-Balance Checker

Checks whether a Monte Carlo algorithm obeys detailed balance, the condition it needs to correctly sample its target distribution, and returns an exact and deterministic PASS or FAIL rather than a statistical estimate.

Built first in Mathematica, then rewritten in Julia, it grew out of PhD work certifying novel Monte Carlo algorithms for protein self-assembly.

Julia · Lean · Wolfram Language

Single-Molecule Computation through Machine Learning

Temporal Classifier

The temporal classifier is a designed chemical reaction network that folds only when acidity arrives in one specific order, not under a reversed, sustained, or resting signal. I trained its reaction rates end-to-end with automatic differentiation in JAX.

I then reproduced the same behaviour in a three-dimensional Brownian-dynamics polymer with explicit charge geometry, confirming the classification survives the move from an idealised well-mixed model to real spatial dynamics. The work sits at the centre of my PhD research on kinetically controlled molecular memory.

Python · JAX · Diffrax

Contact

Get in touch

Available for consulting engagements, research collaborations, and conversations about biosensing, computational science, or creative technology.

[email protected]