All University of Bristol researchers (from PhD student and up) are entitled to a day of free data science support from the Ask-JGI helpdesk. Just email ask-jgi@bristol.ac.uk with your query and one of our team will get back to you to see how we can support you. You can see more about how the JGI can support data science projects for University of Bristol based researchers on our website.
We support queries from researchers across all faculties and in this blog we’ll tell you about some of the researchers we’ve supported from the Faculty of Health and Life Sciences here at the University of Bristol.
Aerosol particles
A researcher approached us with Python code they’d written for simulating radioactive aerosol particle dynamics in a laminar flow. For particles smaller than 10 nanometers, they observed unexplained error “spikes” when comparing numerical to analytical results, suggesting that numerical precision errors were accumulating due to certain forces being orders of magnitude smaller than others for the tiny particles.
We provided documentation and advice for implementing higher-precision arithmetic using Python’s ‘mpmath’ library so that the researcher could use their domain knowledge to increase precision in critical calculation areas, balancing computational cost with simulation accuracy. We also wrote code to normalise the magnitude of different forces to similar scales to prevent smaller values from being lost in the calculation.
This was a great query to work on. Although Ask-JGI didn’t have the same domain knowledge for understanding the physics of the simulation, the researcher worked closely with us to help find a solution. They provided clear and well documented code, understood the likely cause of their problem and identified the solutions that we explored. This work highlights how computational limitations can impact the simulation of physical systems, and demonstrates the value of collaborative problem-solving between domain specialists and data scientists.
Training/course development
The JGI offers training in programming, machine learning and software engineering. We have some standard training courses that we offer as well as upcoming courses being development and shorter “lunch and learn” sessions on various topics.
Queries have come in to both Ask-JGI and the JGI training mailbox (jgi-training@bristol.ac.uk) asking follow up questions from training courses which people have attended. Additionally, requests have come through for further training to be developed in specific areas (e.g. natural language processing, advanced data visualisation or LLM useage). The JGI training mailbox is the place to go, but Ask-JGI will happily redirect you!
Network visualization
Recently Ask-JGI received a query from a PhD researcher in the School of Geographical Sciences. The Ask JGI team offered support on exploring visualisation options for the data provided, and provided example network visualisations of the UK’s industries’ geographical distribution similarity. Documented code solution was also provided so that further customisation and extension of the graphs is possible. At the Ask JGI, we are happy to help researchers who are already equipped with substantive domain knowledge and coding skills to complete small modules of their research output pipeline.
Spin Network Optimisation
The aim of this query was to accelerate the optimization of a spin network which is a network of nodes coupled together by a certain strength, to perform transfer of information (spin) from one node to another by implementing parallel processing. The workflow involved a genetic algorithm (written in Fortran and executed via a bash script) and a Python-based gradient ascent algorithm.
Initial efforts focused on parallelizing the gradient ascent step. However, significant challenges arose due to the interaction between the parallelized Python code and the sequential execution of the Fortran-based Spinnet script.
Code refactoring was undertaken to improve readability and introduce minor speed enhancements by splitting the Python script into multiple files and grouping similar function calls.
Given the complexity and time investment associated with these code modifications, it was strongly recommended to explore the use of High-Performance Computing (HPC) facilities. Running the current code on an HPC system went on to provide the desired speed improvements without requiring any code changes, as HPC is designed for computationally intensive tasks like this.
Grant development
The Ask-JGI helpdesk is the main place researchers get in contact with the JGI with regards to getting help with grant applications. The JGI can support with grant idea development, giving letters of support for applications and costing in JGI data scientists or research software engineers to support the workload for potential projects. You can read more about how the JGI team can support grant development on the JGI website!