In this case study, we hear from Sarah Berger, a researcher working in Bioinformatics, who has been using BlueBEAR to develop proteins that can bind to metals. Magnetic resonance imaging (MRI) is an essential diagnostic tool, particularly powerful when combined with contrast agents. Most state-of-the-art MRI contrast agents are based on the metal gadolinium, which has intrinsic physical … Continue reading “De Novo Protein Engineering: Future-Proofing MRI Contrast Agents with BlueBEAR”
Category: Case study
May 2026 BEAR Newsletter
Birmingham Environment for Academic Research (BEAR) Newsletter Members of the team attended a great BEAR PGR Conference at the end of April on the theme of AI, research integrity and ethics. There were some really thought-provoking talks on the implications of AI and some interesting examples of PhD research from across the university. The event was organised … Continue reading “May 2026 BEAR Newsletter”
Using AI to Bring Indigenous Storytelling Character Figures into Chemistry Education
In this blog, we hear from Dina, a second-year Ph.D. student in Chemical Education, School of Chemistry, who won the best short talk at the BEAR conference 2026. Dina, conducted research that intersects chemistry education, technology, and ethnochemistry. Ethnochemistry is a multidisciplinary field that explores the relationship between chemistry and the traditional wisdom, practices, and … Continue reading “Using AI to Bring Indigenous Storytelling Character Figures into Chemistry Education”
Learning from Nature: Using HPC to Design Efficient Jet Propulsion
In this case study, we hear from Yukesh Karki, a doctoral student from Aerospace Engineering in the School of Metallurgy and Materials, who used BlueBEAR to identify the optimal three-dimensional nozzle geometry for hydrodynamic jet propulsion. He is also the winner of ‘best talk’ at the BEAR Conference 2026. Nature has already evolved highly efficient methods … Continue reading “Learning from Nature: Using HPC to Design Efficient Jet Propulsion “
Research project: Exploring Julia for High-Performance Computing
This project was initiated and led by Dr Vincenzo Brachetta and carried out by PhD researcher Ritesh Moon at the University of Birmingham. Conducted between January and February 2026, it evaluated the performance and practical usability of Julia on BlueBEAR, the University’s institutional high-performance computing (HPC) platform. BlueBEAR supports multi-core CPU workloads, distributed execution across nodes, and GPU-accelerated computation, with … Continue reading “Research project: Exploring Julia for High-Performance Computing”
Understanding multi-agent learning through large-scale simulations
In this case study we hear from Tuo Zhang, a researcher working in Machine Learning, who has been using BlueBEAR to run large-scale simulations of multi-agent reinforcement learning (MARL) algorithms. His research focuses on understanding how learning agents behave when interacting with each other in complex and changing environments. In many real-world systems, decision-making is not performed … Continue reading “Understanding multi-agent learning through large-scale simulations”
Modelling Birmingham’s Cultural Ecology and Urban Oral History Using BlueBEAR
In this case study, we hear from Jack (Wei-Chieh Tsai), a doctoral student from History of Art and Geography who used BlueBEAR to examine how cultural intermediaries, including artists, curators, and cultural organisations, have contributed to urban development. My PhD research examines the role of artistic interventions in transforming post-industrial Birmingham between 1986 and 2016. The project … Continue reading “Modelling Birmingham’s Cultural Ecology and Urban Oral History Using BlueBEAR”
Binary classification of lung tissue immunofluorescence images by deep learning
In this case study we hear from Ellen Jenkins, a postdoctoral student from the Institute of Inflammation and Ageing. Ellen is looking into developing a deep learning model to automatically differentiate the tissue from the air space. There is an ongoing project in the respiratory research group (CMH, IIA) which utilises samples of human lung … Continue reading “Binary classification of lung tissue immunofluorescence images by deep learning”
Modelling accelerator-based neutron sources using the BlueBEAR cluster
In this case study we hear from Louis Butt, a doctoral researcher from Metallurgy and Materials, who has been using BlueBEAR to research accelerator-based neutron sources. I am a PhD student researching accelerator-based neutron sources in the School of Metallurgy and Materials. My work involves taking measurements with our source at the University’s MC40 Cyclotron … Continue reading “Modelling accelerator-based neutron sources using the BlueBEAR cluster”
The value of version control
The Research Software Group’s mission is rooted in the observation that most current research requires software, often written by researchers themselves, and that the application of a few core software engineering principles leads to more effective research. This is neatly captured by the Software Sustainability Institute‘s tag line: “better software, better research”. A core technology … Continue reading “The value of version control”