Final-year PhD in ML & Neuromorphic Computing, finishing up soon in Feb 2026.
I build efficient ML systems for complex sensor data. Currently applying SNNs to real-time anomaly detection in radio astronomy, including training SoTA models and deploying them to neuromorphic chips.
I have previous experience working for the Square Kilometre Array (SKA) building high-performance computational workflow systems, and small-scale consulting in various full-stack development projects.
Looking for ML engineer / applied scientist roles - remote preferred but happy to travel regularly for stints abroad.
For what it's worth, I've also come across this problem - so I made my own solution.
I call it Mondage [0], it looks like a plain todo list app, but lets you drag tasks on top of each other to set dependencies.
Tasks you can do first get sent to the top. Everything else is shown underneath.
I like graph views to get an overview, but when I'm in the weeds, a list is what I want.
The web version is live, I have Android and iOS clients built too, but only in beta release. With enough interest, I'll add full scheduling and other features, but for now, I'm keeping it simple and free. It's a little rough around the edges, but hopefully someone else can find it useful too.
The space is astonishingly crowded, and while that makes things hard to stand out or get noticed, it suggests to me that no one has properly solved this sort of problem - or that it's too personal to solve properly.
As a software engineer working in an astronomy institute, it's nice to see the excitement around the outputs of this project. It's pleasing to see an intersect between people enjoying the image, and discussing some of the technical details.
I know it's done this way to be consistent with the other use-case pages, but it seems really interesting to show a proposition for which only very few people could actually seriously consider, yet anyone can register their interest; pretty neat.
Remote: Yes
Willing to relocate: Short-term trips ok
Technologies: Python, PyTorch, TensorFlow, OpenCV, SNNs, LLM APIs, Django, Kubernetes, Fly.io, Docker, Kubernetes, Git, C/C++, HPC, MPI, Neuromorphic Computing
Resume: https://contact.nicpritchard.com/files/Resume_Pritchard_2025...
Email: professional [at] nicpritchard.com
Final-year PhD in ML & Neuromorphic Computing, finishing up soon in Feb 2026. I build efficient ML systems for complex sensor data. Currently applying SNNs to real-time anomaly detection in radio astronomy, including training SoTA models and deploying them to neuromorphic chips.
I have previous experience working for the Square Kilometre Array (SKA) building high-performance computational workflow systems, and small-scale consulting in various full-stack development projects.
Looking for ML engineer / applied scientist roles - remote preferred but happy to travel regularly for stints abroad.