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promotions process. About You Completion or near completion of a PhD in computer science, information visualisation, visual analytics, human-centred computing (HCI), spatial data science, or a closely related
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involving extensive use of GC/MS analytical equipment for bioanalytical mass spectrometry, including advanced small molecule analysis, data interpretation, and assay development. You can demonstrate strong
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analytical chemistry, particularly GC-MS analysis of trace volatiles Good communication and problem-solving skills Knowledge in data analytics (python or R) is desirable Knowledge in atmospheric chemistry is
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-controlled analytical methods, and conduct targeted, suspect, and non-target analyses. This includes performing MS/MS experiments, interpreting high-resolution mass spectrometric data, and undertaking
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will hold demonstrated experience in epidemiological methodologies and data analytics. Your skills will include critical appraisal of epidemiological evidence, and statistical analysis to evaluate large
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Generative AI model which will predict the fertility stages of species based on analytical information from blood (or body fluid) samples. The successful candidate will work closely with the project Chief
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maintaining analytical and purification equipment. Methodical approach to problem solving and a meticulous attitude to laboratory performance, record keeping, electronic data storage and organisation. Excellent
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leading clinicians and researchers tackling real‑world challenges in critical care, data innovation, AI and advanced analytics. We are seeking a talented Data Scientist / Clinical Data Engineer
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, conference papers and/or reports, or professional or technical contributions which provide evidence of strong research potential. Sound analytical skills with an ability to communicate complex information
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establish a distinctive research profile, with a particular focus on Green Energy Investment and Trade in Asia. The role will suit a candidate with strong data analytical capabilities, demonstrated knowledge