-
bio-optical (fluorescence and backscatter) data from a 2025 research expedition to the Bellingshausen Sea, West Antarctica, coupled with data from laboratory analyses of algal pigments, particulate and
-
, are crucial for modelling volcanic processes and are vital for understanding the transitions. Geophysical monitoring provides essential information to constrain these parameters and inform decision
-
data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
-
. Describe site connectivity along global flyways, using a global dataset of important areas for seabirds (i.e., Key Biodiversity Areas) and data from the STD. Investigate the drivers of flyway connectivity
-
on the topic (2,4). Training and Development Training will maximise future employability in academia and industry: Programming and geospatial data analysis using Python/R. Machine/deep learning techniques
-
spectroscopy, and gas chromatography. Advice on scientific communication, writing, and data analytics will be provided. Presentation of data at national and international conferences is encouraged and the PGR
-
(or related) Mode of Study Full-time Start Date 1 October 2026 Funding Information ARIES studentships are subject to UKRI terms and conditions . Successful candidates who meet UKRI’s eligibility criteria will
-
Information ARIES studentships are subject to UKRI terms and conditions . Successful candidates who meet UKRI’s eligibility criteria will be awarded a fully-funded studentship, which covers fees, maintenance
-
to prostate cancer progression. This information will support the setting up of a clinical trial where anti-microbial agents are used to prevent prostate cancer development, resulting in significant