162 augmented-workers-using-smart-robats-in-manufacturing-cell Postdoctoral positions at University of Oxford
Sort by
Refine Your Search
-
The post holder will develop computational models of learning processes in cortical networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity
-
With the human population estimated to reach 9.8 billion people by 2050, the looming nitrogen (N) crisis, stemming from the intensive use of fertilisers in agriculture, requires urgent global action
-
hold or be close to completion of a relevant PhD/DPhil, together with experience of research on Tibetan History; experience and skills in the translation of classical Tibetan, as used in administrative
-
, extreme events (e.g. heatwaves, droughts, floods, etc.), and their attribution, as well as related health, developmental and socio-economic impacts. The successful candidate will play a key role in
-
, Oxford, Leeds, Reading, and Birmingham) and international (Utrecht University, ETH Zurich, Université Catholique de Louvain, etc.) scientists to use new modelling resources and methods to elucidate drivers
-
The University of Oxford is a stimulating work environment, which enjoys an international reputation as a world-class centre of excellence. Our research plays a key role in tackling many global
-
Raman’s cardiovascular research team. This role is embedded within a cutting-edge programme focused on integrating high-dimensional datasets, including advanced cardiac MRI (oxygen-sensitive, metabolic, and
-
to the role, as well as those generic to a grade 7 postholder. Informal enquiries are very welcome and can be addressed to Dr Marco Springmann (marco.springmann@ouce.ox.ac.uk). This post is fixed-term until 31
-
Institute. This role is especially suitable for someone with strong formal reasoning and data analysis skills who is considering progression to a PhD or further postdoctoral research in AI ethics, social
-
and evaluation. The post holder will take a leading role in advancing theoretical and algorithmic research in the domain of probabilistic preference aggregation, contribute to the design and analysis