Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
on expectations elicited via tailored household and firm surveys (carried out by another team member) and other spatial and physical climate risk data. The goal of this agent-based modeling is to identify
-
of large spatial and temporal biodiversity datasets. Since almost 20 years the Rhine-Main-Observatory (RMO; https://www.senckenberg.de/rmo/ ) has been part of the German LTER network (https://www.ufz.de/lter
-
. The research in the PhD project will focus on core spatio-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation
-
challenging conditions (see https://tissueresilience.com ). Harnessing powerful in vivo models, our work spans multiple biological scales - linking the molecular cell biology of individual cells to the health
-
ACCE+ DLA programme: Landscape-scale drivers and limits of endangered species spatial and temporal distribution School of Biosciences PhD Research Project Competition Funded Students Worldwide Prof
-
application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes
-
found at https://accedtp.ac.uk/, in the ‘prospective applicants’ tab. Project overview Are you interested in a PhD working on the biological impacts of climate change, based in world-leading research
-
Research Infrastructure? No Offer Description Position available within the research project entitled: “Diachronic modeling of (bio)climate conditions at a fine spatial scale in the main cities of North-East
-
, or glaciology. We invite applicants to highlight experience with spatial analysis tools, such as GIS, or other quantitative approaches, which could include modeling or AI. The teaching load is three courses per
-
Mathematics and Statistics we conduct research within the theory and implementation of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational