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Senior Machine Learning Researcher at ASTeC (STFC/UKRI)
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Assessing your cultural and operational fit
PhD in Computer Science from the University of Manchester, focusing on Machine Learning. Upon completion, I immediately joined ASTeC to do applied machine learning research for particle accelerators. My work is currently focused on AI based control systems for accelerator technologies and anomaly detection.
The Manchester Metropolitan University
Bachelor of Science (BSc), Computing
January 1, 2010 – January 1, 2013
The University of Manchester
Doctor of Philosophy - PhD, Computer Science
N/A – Present
STFC
Senior Machine Learning Researcher
October 1, 2025 – Present
STFC
Machine Learning Researcher
January 1, 2021 – Present
The University of Manchester
PhD Artificial Intelligence
July 1, 2015 – June 1, 2020
Manchester Area, United Kingdom
AP Softworks
Freelance Software Developer
February 1, 2014 – January 1, 2021
Manchester Area, United Kingdom
Teledata UK Ltd
Systems Developer
March 1, 2012 – November 1, 2013
Manchester Area, United Kingdom
Ebotech Consulting Ltd.
Software Developer
August 1, 2011 – January 1, 2012
Cultural Fit Analysis
The candidate's career trajectory shows a clear progression from general software development to specialized AI/ML research, aligning well with a target role of ML Engineer. The academic background (PhD) and research roles suggest a culture of continuous learning and deep technical exploration. The diversity of roles, from freelance to institutional research, indicates adaptability. However, without project details or team-based experience descriptions, a deeper assessment of cultural fit is limited.
Soft Skills & Operational Fit
The candidate's resume indicates a strong research-oriented background, suggesting analytical thinking and problem-solving skills. The freelance and systems developer roles imply adaptability and practical application of technical knowledge. However, specific soft skills like teamwork, leadership, or communication in a corporate setting are not explicitly detailed in the provided data.