Daniel Cutting Email & Phone Number
@exscientia.co.uk
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Who is Daniel Cutting? Overview
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Daniel Cutting is listed as Machine Learning for Drug Discovery at Valence Labs, based in Oxford, England, United Kingdom. AeroLeads shows a work email signal at exscientia.co.uk and a matched LinkedIn profile for Daniel Cutting.
Daniel Cutting previously worked as Senior Machine Learning Research Engineer at Valence Labs and AI Research Scientist at Exscientia. Daniel Cutting holds Doctor Of Philosophy - Phd, Theoreticalphysics from University Of Sussex.
Email format at Valence Labs
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AeroLeads found 1 current-domain work email signal for Daniel Cutting. Compare company email patterns before reaching out.
About Daniel Cutting
Senior Machine Learning Research Engineer at Valance Labs, working on revolutionising drug design with Artificial Intelligence. Former postdoctoral researcher and scientific software developer researching the early Universe using custom built massively parallel simulation codes. Research topics include gravitational waves, phase transitions, relativistic hydrodynamics and turbulence.Over 8 year's experience programming in C/C++ and Python, with a focus on machine learning, high performance computing, numerical simulations and data analysis. Highly numerate with strong mathematical skills developed over a PhD in Theoretical Physics and as a postdoctoral researcher.Interested in the machine learning and data science revolution and how these techniques can be leveraged to innovate in science and improve people's lives.
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Daniel Cutting work experience
A career timeline built from the work history available for this profile.
Ai Research Scientist
- Designing and applying AI models to accelerate drug discovery for biologics and small molecules.
- Led a team building novel generative methods for de novo antibody design.
- Developer in the team that built Exscientia’s virtual screening pipeline for developable antibody binders.
- Developed AbMPNN, an antibody specific inverse folding model. Deployed and used AbMPNN for hit expansion in the Biologics pilot study.
- Created an antibody-specific diffusion model, IgDiff by fine-tuning a public model on antibody data. Demonstrated that IgDiff generates novel and designable antibody structures.
- With collaborators published a study benchmarking the performance of docking tools for predicting antibody-antigen binding poses when using AI predicted antibody models.
Postdoctoral Researcher
- Responsibilities included:
- Conducting world leading research in early Universe physics, with a focus on numerical simulations and relativistic hydrodynamics.
- Maintainer and developer for several HPC applications for studying gravitational wave production in the early Universe. These codes have been used to produce publications in some of the leading journals in the field.
- Presenting research seminars and conferences internationally, including as a plenary speaker at the inaugural European Consortium for Astroparticle Theory Symposium.
- Full member of the LISA Consortium, an upcoming European Space Agency mission.
- Co-supervisor for BSc and MSc students, with research projects leading to publications.
Physics Phd Student
- Researching first-order phase transitions in the early Universe.
- Lead developer of a massively parallel MPI C++ simulation code studying vacuum transitions.
- Core developer of a massively parallel MPI C simulation code studying a thermal phase transition using relativistic hydrodynamics.
- Experienced with using Python to analyse terabytes of data generated during production runs comprising millions of CPU hours.
- Presented research at multiple high-level international conferences and universities around the world.
- Published in prestigious journals, Physical Review Letters and Physical Review D.
Associate Tutor
Delivered workshops and marked coursework on the Master level module "Programming in C++" and the second year undergraduate module "Thermal and statistical physics".
Earth Observation Gradnet Internship
Implemented and explored the utility of several deep learning models to identify fields of coffee in Brazil using Sentinel 2 satellite imagery. Performed exploratory data analysis for monitoring coffee crop health and fruit ripeness.Technologies included AWS, TensorFlow, keras, geopandas, eo-learn, and sentinel-hub.
Summer Research Student
- Took part in research placements over the Summers in undergraduate degree at the University of Sussex.First research placement:
- Studied the wavefunction of a graviton travelling in a 5-dimensional Anti-de Sitter metric and Kaluza-Klein theory.Second research placement:
- Worked with a professor on a smoothed-particle hydrodynamic code intended to simulate flooding.
- Developed visualisation methods for a smoothed-particle hydrodynamics simulation program.
- Created a comprehensive user manual detailing installation and how to use the program.
- Ran tests comparing program simulations for various fluid flows against theoretical predictions.
Daniel Cutting education
Doctor Of Philosophy - Phd, Theoreticalphysics
Mphys, Physics, First-Class Degree
Frequently asked questions about Daniel Cutting
Quick answers generated from the profile data available on this page.
What company does Daniel Cutting work for?
Daniel Cutting works for Valence Labs.
What is Daniel Cutting's role at Valence Labs?
Daniel Cutting is listed as Machine Learning for Drug Discovery at Valence Labs.
What is Daniel Cutting's email address?
AeroLeads has found 1 work email signal at @exscientia.co.uk for Daniel Cutting at Valence Labs.
Where is Daniel Cutting based?
Daniel Cutting is based in Oxford, England, United Kingdom while working with Valence Labs.
What companies has Daniel Cutting worked for?
Daniel Cutting has worked for Valence Labs, Exscientia, University Of Helsinki, University Of Sussex, and Earth-I.
How can I contact Daniel Cutting?
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What schools did Daniel Cutting attend?
Daniel Cutting holds Doctor Of Philosophy - Phd, Theoreticalphysics from University Of Sussex.
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