-
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
-
supervision across the Schools of Chemistry, Pharmacy & Pharmacology and of Environmental Sciences, gaining experience in both laboratory and computational approaches. You will benefit from two 3-months
-
developing a new lab to assist in characterisation of multispectral reflectance of materials. Research methodology The student will utilise the existing VL database of key materials, but importantly will also
-
Specification We seek an enthusiastic individual who is interested in marine ecology, computing, with some prior experience in programming and data handling, eager to communicate findings to wider stakeholders
-
candidate highly employable, in industry or academia. Entry Requirements At least UK equivalence Bachelors (Honours) 2:1. English Language requirement (Faculty of Science equivalent: IELTS 6.5 overall, 6 in
-
(optional). Person specification: Prior experience in computer coding (e.g., Python, SLiM), AI modelling, and understanding of evolutionary or conservation genetics / genomics is desirable. Good teamwork
-
observations and modelling of the physics and biogeochemistry of Antarctic shelf seas. You will gain experience in computer coding, statistics for environmental science, working with and piloting autonomous
-
. Bioinformatics: Comparative genome analysis, detection of selection, and functional genomics, phylogenetics. Computational skills: UNIX/Linux, HPC computing, and programming in R and Python. You will gain hands
-
NERC. Person Specification We seek an enthusiastic individual with a degree in geoscience, physical sciences, or computer science. Numerical literacy and experience with coding tools (Matlab or Python
-
strong scientific interests and self-motivation. They will have a degree in physics, mathematics, oceanography, meteorology, or a related science with good computing and numerical skills. Entry