6 Postdoctoral Fellowship at The University of Sussex, East Sussex, United Kingdom

The post provides an outstanding opportunity to develop and apply research skills in developmental neuroscience using a range of techniques pioneered in the lab (calcium imaging, thermo-/opto- genetics, CRISPR/cas9, Drosophila behavioural experiments) as well as working with collaborators: Electron microscopy neuronal reconstructions with Prof. Albert Cardona (Univ. of Cambridge and MRC-LMB), and electrophysiology experiments with Prof. Richard Baines (Univ. of Manchester). Candidates with evidence of scientific accomplishment in neuroscience or developmental neurobiology are encouraged to apply. Experience in calcium imaging or electrophysiology analysis are desirable. Experience working with Drosophila would be an advantage. The successful candidate should be capable of working independently on this project, whilst integrated into a highly collaborative and supportive research group, and wider neuroscience community of over 50 neuroscience researchers that organises a wide range of scientific and career development activities.

Are you an FPGA expert looking to use your skills to accelerate cutting-edge AI applications with spiking neural networks? If so, we have an exciting opportunity for a Research Fellow to join the AI group within the Department of Informatics at the University of Sussex. We have many years of experience using GPU hardware to accelerate spiking-neural networks which we have distilled into our GeNN library (https://genn-team.github.io/). However, while GPUs can provide excellent performance on static datasets, they are less suitable for ‘live’ data. FPGAs provide an exciting alternative and have already been shown to be well-suited to spiking neural network simulation. In this project – funded through Dr James Knight’s prestigious EPSRC Research Software Engineering Fellowship – the research fellow will work with the GeNN team to codesign hardware and software for a programmable FPGA accelerator which will be driven by our GeNN software and deployable at scales ranging from the edge to the data-centre.

Our consortium brings together leading teams from the University of Sussex, the University of Loughborough, the National Physical Laboratory and companies from the quantum technology, telecommunication and defense sectors. Our objective is to build a miniaturized portable atomic clock based on a novel interrogation scheme on a single calcium ion, with an accuracy at the 10^-14 level or better. At ITCM, we have developed a novel interrogation scheme for ion-based atomic clocks that promises significantly improved robustness compared to conventional optical atomic clocks. The project aims to demonstrate the novel scheme in an existing system, implement the system on an existing portable system and demonstrate its advantages in real-world settings.

Applications are invited for a two-year fixed-term NIHR Postdoctoral Research Fellow in dementia based at the Centre for Dementia Studies, Brighton and Sussex Medical School. The post is funded by the NIHR Applied Research Collaboration Kent Surrey Sussex (ARC KSS) to build dementia research capacity regionally and will be appointed to work within the Living Well with Dementia Theme. Applications are welcome from those with a range of backgrounds including academic researchers and those with experience of delivering clinical services for people living with dementia. The post holder will benefit from support across the ARC KSS themes and a national peer cohort of dementia researchers across the 15 ARCs nationally to build his/her research career and leadership skills. The post holder will provide direct research support to Professor Naji Tabet in his work as ARC KSS Dementia Theme Lead. The post holder will conduct research in line with the Living Well with Dementia portfolio of research. The dementia research topics undertaken will include researching approaches to support people to live well with their dementia.

Trapped ions are one of the most mature implementations to deliver practical quantum technologies. We have developed a unique approach for trapped-ion quantum computing that enables scaling to a large number of qubits. The approach couples scalable global microwave based quantum gate technology with fully integrated quantum computing microchip modules that can be linked together using fast electric field links. This position is part of a larger effort to develop and operate quantum computing solutions which scale to significantly larger system sizes. We currently operate 5 quantum computer prototypes in our lab and the position will focus on one or multiple of these experimental setups directed towards the implementation of quantum error correction, ion transport and quantum gate execution, raising gate fidelities, operation of multi-module quantum computing prototypes and the development of quantum computing microchips.

Although there have been major advances in treatments for B cell malignancies, heterogeneity both between and within diseases contribute to the variable responses to current therapies. Therefore, there is an urgent need for personalised strategies to accurately predict the optimal drug/drug combination for an individual patient. Aberrant NF-κB transcription is a major player in B cell malignancies and is activated by numerous signalling pathways within the tumour microenvironment (BCR, TLR9, CD40L etc) resulting in proliferation and upregulation of anti-apoptotic proteins. The NF-κB signalling network is comprised of multiple components, which can be activated by different stimuli, giving rise to distinct NF-κB states. We have developed a novel flow cytometry-based NF-κB fingerprinting assay and demonstrated distinct expression patterns between and within different CLL patient samples and DLBCL cell lines. We propose that these different NF-κB fingerprints, coupled with nuclear NF-κB subunit activity, and global gene transcription states, are the key to identifying therapeutic vulnerabilities in individual tumours. The project will generate experimental data, using primary CLL cells and DLBCL cell lines, to create a library of NF-κB signalling states, and then use this library to inform mechanistic mathematical modelling/simulations. The ultimate goal of this interdisciplinary project is to exploit computational models to accurately identify the ‘right drug(s) for the right patient’ and then experimentally test these predictions in the laboratory using patient-derived tumour samples.