Charles Phillips, PhD

Principal Solution Scientist

Intellegens · Cambridge, UK · February 2026 – Present

Technical and scientific lead for customer engagements - delivering bespoke computational solutions and automation frameworks tailored to custom infrastructure and research workflows.

• Design and implement multi-modal data pipelines across experimental sources and vendor platforms, integrating custom processing into Alchemite™ modelling workflows
• Develop and deploy automated detection and mitigation for customer-specific data quality and integration issues through trials and pilot assessments
• Deliver live technical demonstrations globally, translating ML architectures and outputs into insights aligned with customer research objectives
• Identify proof-of-concept extensions with market potential and collaborate with development and commercial teams to scale them into product features
• Drive platform performance improvements and expansion opportunities with named accounts across materials, chemicals, and life sciences

Technical highlights: Multi-modal pipelines · Alchemite™ integration · Solution architecture · Enterprise scientific delivery

Principal Life Science Innovation Lead

Intellegens · Cambridge, UK · October 2025 – February 2026

Led strategic direction and delivery of the Alchemite™ Oligonucleotide software solution - full conceptualization-to-deployment lifecycle with scalable workflows aligned to industrial requirements.

• Coordinated technical and commercial leadership to drive rapid market adoption and secure adoption by major industry partners
• Supported customer teams from early-stage research through late-phase development
• Alchemite™ Oligonucleotide programme contributed to Intellegens being named a finalist for Life Science Company of the Year (2026 Cambridge Independent Science & Technology Awards)

Technical highlights: Product strategy · Oligonucleotide manufacturing ML · Pharma & biotech partnerships · Go-to-market delivery

Machine Learning Scientist - R&D

Intellegens · Cambridge, UK · May 2024 – September 2025

Lead scientific and technical developer of the Alchemite™ solution for oligonucleotide manufacturing - end-to-end development from scientific strategy through technical implementation and project execution.

• Directed development of ML solutions for biopharmaceutical R&D and manufacturing (synthesis, purification, analytics)
• Drove end-to-end customer project support across diverse data types and domains including materials science, life sciences, and manufacturing
• Contributed to core Alchemite™ platform innovation - robustness, scalability, and impact on complex, noisy experimental data
• Co-authored and presented recorded webinar on accelerating oligonucleotide process development with ML

Technical highlights: Alchemite™ · Oligonucleotide SPOS · Active learning · High-dimensional sparse data · Customer R&D delivery

Doctoral Researcher - Theoretical & Computational Chemistry

University of Cambridge · Collepardo Research Group · October 2020 – February 2024

Member of Professor Rosana Collepardo-Guevara’s group, developing multi-scale computational models of genome structure and chromatin organisation at the nanoscale. Thesis: “Dissecting the Architectural Properties of Chromatin and the Influence of the H1 Linker Histone on Chromatin Regulation.”

Investigated how intrinsic nucleosome properties, epigenetic modifications, and architectural proteins regulate chromatin across functionally distinct domains - linking molecular detail (H1, nucleosomes, epigenetics) to mesoscale “liquid-like” organisation using the lab’s mechanistic multiscale chromatin model.

• Extended chemically specific coarse-grained chromatin models (Python, C++, LAMMPS) for phase behaviour and linker histone H1 effects
• Created custom enhanced-sampling methods; collaborated internationally with experimental groups
• Computational work underpinning Science Advances (2026) front-cover paper on H1 as a liquid-like chromatin glue

Technical highlights: Multiscale chromatin MD · Phase separation · Epigenetics · Enhanced sampling · Scientific C++

MPhil in Scientific Computing

University of Cambridge · Department of Physics · 2019 – 2020

Thesis: “Computational Physics of Chromatin: Effects of DNA Linker Length on Liquid–Liquid Phase Separation of Chromatin.”

• Distinction - short project: “Chromatin Compaction as a Function of Nucleosome Repeat Length”
• Distinction - short project: “Mid-Resolution Coarse-Grained Model for Oligonucleotides”

Selected courses: C++ for Scientific Computing · Software Design · Data Visualisation · Atomistic Modelling of Materials · Electronic Structure & DFT · Introduction to Quantum Mechanics · Mesoscale Coarse-Grained Modelling

Research Assistant / Intern

Huntsman Corporation · Everberg, Belgium · August 2017 – August 2018

• Polymer science research leading to granted patent WO2021175730A1
• Developed synthesis routes and characterised materials (rheology, spectroscopy, mechanical testing)
• Awarded the highest grade ever given to a research intern at the site