Welcome
Hi, I'm William - a Physicist, Cloud Engineer, and Entrepreneur.
👋 About me
Read more about me
As a passionate computational physicist, my journey in this field is a blend of my early fascination with computers and a growing love for mathematics and physics. My approach to programming is deeply influenced by physics principles and harnessing the power of parallel computing for optimal performance.
My transition from just a computer enthusiast to a passionate follower of physics was not just a change in interest, but a journey enriched by the wisdom of mentors and tutors. Their guidance has been instrumental in shaping my understanding and approach.
At the core of my academic pursuits lies a relentless curiosity to understand the 'why' behind phenomena. Physics, to me, is not just a field of study; it's a philosophy that aligns perfectly with my quest for reasons and rationale. This philosophy drives me to build upon the work of my peers, aiming to unravel answers to some of the most perplexing questions.
Beyond my professional endeavours, I am committed to lifelong learning. Whether it's exploring new programming techniques or delving into a complex physics concept, I find joy in continually evolving and striving to be the best version of myself. This dedication to growth is not just a hobby but a way of life.
View my CV.
Contact: william.e.doyle.contact@gmail.com
👨💻 Professional Experience
☁️ Cloud Engineer
Led Infrastructure Transformation: Managed 10+ production environments using Terraform, overseeing GKE, EKS, AKS, and VPCs, and integrating S3 for state management. Significantly enhanced deployment speed and reliability for clients, including Shell.
Multi-Platform Expertise: Gained substantial experience in GCP, AWS, and Azure by deploying and managing resources through Terraform IaC on these platforms.
Containerization and Orchestration: Proficient in Linux, Kubernetes (handling deployments, replica sets, services, ingresses) and Docker for creating and managing pods.
DevOps Practices: Utilised CI/CD via GitHub Actions for testing and versioning, and developed automation scripts in Bash, Python, and JavaScript, significantly improving process workflows.
Monitoring and Security: Enhanced system integrity and reduced downtime by implementing Grafana monitoring and robust security protocols.
Team Collaboration: Fostered excellent teamwork and innovation through collaboration across teams and pursuing continuous learning to broaden technical ability.
🛠️ GitHub Projects
Title | Description | Stars | Tech |
---|---|---|---|
GravAD | Gravitational Wave Analysis using Auto Differentiation with JAX | ||
StellarPhysicsHub | Flask-based web application designed for astronomy enthusiasts in Python | ||
PS1Palette | Streamline Bash PS1 customisation through script automation for prompt colour coding and .bashrc integration. | ||
CBC-Simulation | Simulating CBCs with a focus on GWs emission during the inspiral phase using classical mechanics | ||
StarScholar3D | Dynamic 3D Visualisation of Stars Using The Yale Bright Star Catalogue in Python | ||
portfolioWebsite | THREE.js website with animation on scroll | ||
solarSystem | a JavaScript simulation using the p5.js library to model a basic solar system | ||
FluidSim | PyGame 2D Fluid Simulation | ||
PythonProjectInit | Python Project Initialisation Automation through Shell Scripting | ||
nordvpn-polybar | NordVPN polybar integration using BASH script | ||
AstroClassifierML | Machine Learning used on SDSS Data to Classify Stars, Galaxies and Quasars | ||
PyWaveCNN | Convolutional Neural Network for Categorising Gravitational Wave Contours | ||
StellarSpectraML | Machine learning project classifying stellar spectra using TensorFlow and astronomical datasets | ||
TESCOdle | A Wordle-Style Tesco Product Pricing Game | ||
tesco-webscraper | Using Selenium to Webscrape Tesco for Products, Prices and Images | ||
TUITS | Terminal User Interface Time Sheet - with AI Summary |
⚛️ Publications
Searching for Black Holes using Auto Differentiation | View Publication |
Advancements in the GravAD Pipeline: Template Reduction and Testing Simulated Signals for Black Hole Detection | View Publication |
ResearchGate Profile | Visit Profile |
📜 Certificates
Course ▼ | Provider ▼ | Specialisation ▼ |
---|---|---|
DeepLearning.AI TensorFlow Developer | Coursera | Python, TensorFlow, Machine Learning |
Sequences, Time Series and Prediction | Coursera | Python, TensorFlow, Machine Learning |
Natural Language Processing in TensorFlow | Coursera | Python, TensorFlow, Machine Learning |
Convolutional Neural Networks in TensorFlow | Coursera | Python, TensorFlow, Machine Learning |
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning | Coursera | Python, TensorFlow, Machine Learning |
Intermediate Machine Learning | Kaggle | Python, Machine Learning |
Intro to Machine Learning | Kaggle | Python, Machine Learning |
Learn SQL | Codecademy | SQL, Data Management |
Analyze Data with SQL Skill Path | Codecademy | SQL, Data Analysis |
How to Transform Tables SQL Course | Codecademy | SQL, Database Transformation |
How to Analyze Business Metrics with SQL Course | Codecademy | SQL, Business Analysis |
Learn Intermediate SQL for Marketers and Product Managers | Codecademy | SQL, Marketing, Product Management |
Master Statistics with Python Skill Path | Codecademy | Python, Statistics |
Learn Data Analysis with Pandas | Codecademy | Python, Data Analysis |
Learn Git & GitHub | Codecademy | Git, Version Control |
Learn Bash Scripting | Codecademy | Shell Scripting, Command Line |
Certified Kubernetes Administrator | A Cloud Guru | Kubernetes, Cloud |