82 application-forms "https:" "https:" "https:" "Lawrence Berkeley National Laboratory Physics" PhD positions at University of Nottingham
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PhD Studentship: Preclinical modelling and therapeutic targeting of glioblastoma infiltrative margin
revealed distinct gene expression profiles of the infiltrative margin of glioblastoma via bulk transcriptomics https://pubmed.ncbi.nlm.nih.gov/37434262/ predicated on biopsies obtained via 5-aminolevulinic
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confirmed by BBSRC later in the Spring. Applicant Qualification Requirements Applicants should hold a first or upper-second class UK honours degree (or equivalent) in a science-based discipline such as Food
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CDT at the start of the course (October to December inclusive). CDT training will be delivered across the CDT partner universities at Sheffield, Manchester, Birmingham and Liverpool. The training course
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transcripts. These should be submitted via email to Dr Taresco and through the University of Nottingham’s online application system (https://www.nottingham.ac.uk/pgstudy/how-to-apply/apply-online.aspx
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. These should be submitted via email to Dr Taresco and through the University of Nottingham’s online application system (https://www.nottingham.ac.uk/pgstudy/how-to-apply/apply-online.aspx ), selecting “Chemistry
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(ioan.notingher@nottingham.ac.uk ). Application: https://www.nottingham.ac.uk/pgstudy/how-to-apply/apply-online.aspx View All Vacancies
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stipend for 3.5 years, starting at £22,000 pa. A travel and consumables allowance will also be available. Entry Requirements: Starting October 2026, we require an enthusiastic graduate with a 1st class
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to an expert committee from the University of Nottingham as part of a competitive process to secure the funding. How to apply: Fill out this form: https://forms.office.com/e/SxNLR1qbBE?origin=lprLink , answer
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with a 1st class degree in engineering, maths or a relevant discipline, preferably at Masters level (in exceptional circumstances a 2:1 degree can be considered). To apply visit: http
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the integration of high data-density reaction/bioanalysis techniques, organic synthesis, laboratory automation & robotics and machine learning modelling. This exciting project involves the application of innovative