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Field
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bioinformatics programming and high-performance computing environments, including Python, R, Linux-based workflows, and HPC/cloud platforms for reproducible pipeline development. Evidence of strong scholarly
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such as R/Python/Java or similar languages, and familiarity with Unix-based platforms is advantageous Experience working in cloud environments (e.g., AWS) is beneficial High motivation and willingness
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, Open RAN, 6G/NextG); Hands-on experience with cellular network platforms (e.g., O-RAN, srsRAN, OpenAirInterface, Aether/SD-RAN), edge/cloud computing platforms (e.g., Kubernetes, OpenStack), SDN, and/or
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as cloud condensation nuclei and thus indirectly influence the climate. Significant support for this research is provided by the infrastructure of the National Atmospheric Observatory Košetice (NAOK
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modelling of atmospheric chemistry and aerosol-cloud interactions. The successful candidate will work within UNIC to improve knowledge of the interactions between particulate matter emitted by aircraft
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to key, but poorly understood, physical processes and parameterisations. At Exeter, the work will focus on understanding how processes such as clouds and convection, ocean heat transport, and continental
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, cybersecurity, privacy-preserving methods, or distributed systems. Experience with cloud platforms, real-time data processing, or IoT data. Prior research experience and interest in publishing. Physical Demands
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evaluation Knowledge in biology and genomics Experience working with large datasets and numerical computing libraries (NumPy, Pandas, SciPy) Familiarity with Linux environments, version control (Git), cloud
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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analytics-driven research questions that lead to high quality publications. Experience working in interdisciplinary teams spanning clinical, wet-lab, and computational research. Familiarity with cloud