17 parallel-processing-bioinformatics Fellowship positions at UNIVERSITY OF SOUTHAMPTON in United Kingdom
Sort by
Refine Your Search
-
experimentation and thermodynamics calculations. Establish a high-throughput bulk materials processing route to enable efficient characterisation and parallel testing of multiple compositions. Develop a high
-
foundation in fundamental biofilm research, microbial community assembly and manipulation, and biofilm reactor operation is essential. Experience in metabolic engineering is desirable. The successful candidate
-
the opportunity to expand their skills in bioinformatic analyses. The project will focus on the identification of plant genes that can be linked to the host’s microbial community structure and function
-
Justin Sheffield. This project aims to transform our understanding of soil moisture (SM) variability and its interactions with land-atmosphere processes. The project will use cutting-edge modelling, data
-
industry stakeholders and will be responsible for research on distributed query processing and information retrieval for text and RDF files. Experience in Linked Data and Semantic Web technologies is
-
that can be designed and optimised for both passive and active photonic components, allowing for the full suite of device functionality to be incorporated via simple and low-cost processes on a single
-
ion beam nanofabrication processes for advanced photonic materials and devices, so as to enhance their functionality, optical performance and energy efficiency. To be successful in this role, you will
-
knowledge to complement our team. In this role, you will work with others to create glass layers via processes such as flame hydrolysis deposition and various microelectronics and optical fibre fabrication
-
responsible for research on distributed query processing and information retrieval for text and RDF files. Experience in Linked Data and Semantic Web technologies is essential, while familiarity with approaches
-
(e.g., shopping malls). Located at the intersection of machine learning, robotics, and acoustic signal processing, the project will bring together a highly interdisciplinary team of researchers, industry