Sort by
Refine Your Search
-
adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural data to decode multisensory information Investigate how neural
-
visual and auditory cortices using techniques such as cross-modal decoding, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform
-
contributing effectively to a collaborative research team Knowledge, Skills and Experience Experience applying qualitative research methods for data collection (e.g., interviews or focus groups) and analysis
-
research assistant) or extended work/study/travel in a different cultural context Experience and understanding of qualitative data analysis Experience conducting statistical analyses in R Funding Notes Each
-
objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as
-
response have led to targets for reducing overflow frequency, ecological harm, visual impacts, and protecting bathing water. This PhD project has been co-developed with four UK water companies and the
-
of a multidisciplinary team. Core skills include: Proficiency in data analysis and interpretation. Familiarity with research methodologies and clinical guidelines. Strong organisational skills and
-
. Ability to work independently and as part of a multidisciplinary team. Core skills include: Proficiency in data analysis and interpretation. Familiarity with research methodologies and clinical guidelines
-
, Skills and Experience • You will have substantial technical experience in time series analysis, ideally either in neurophysiology data or wearable sensor data • You will have experience of at least