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About the Role We are seeking an enthusiastic and motivated postdoctoral researcher to apply advanced data analytics and machine learning techniques to real-world clinical data in the field of viral
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existing machine learning methods, as well as building robust, well-documented, and reproducible analytics pipelines for long-term use by the wider team. You will carry out data analysis and manage
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completion of a PhD in Psychology or a relevant area along with experience of collecting data from research participants. With excellent data analytic skills, you will be familiar with SPSS and at least one
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of mixed phase numerical or analytical flow modelling for icing. Experience conducting and analysing experimental data is desirable. You should have a record of academic publications in the field and be able
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group : here About you Applicants must hold a PhD Inorganic Materials Chemistry or a related area (or be close to completion), prior to taking up the appointment. The research requires experience in
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to coordinate research activities and meet deadlines in a fast-paced research environment are essential together with strong analytical skills and the ability to interpret complex data. You will have excellent
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responsibilities will include working within clinical researchers associated with the project, taking responsibility for completion of data analysis, and helping with the supervision of PhD students working
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develop an analytical framework to achieve the grant objectives. The post holder will model ecological niches of feeding and breeding grounds in extant whale migratory species, for which occurrence data
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disease. Together with other members of the team, the post-holder will design parallel tasks for rodents and humans and apply comparable analytical approaches to data across species. Cell and circuit
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fractionation (i.e. surface biotinylating, gradient centrifugation, and be proficient in advanced data analysis (i.e. R, Python). Excellent analytical, organisational, and problem-solving skills are essential