Sort by
Refine Your Search
-
generate key structural and biophysical data to support the design of small molecule inhibitors with particular focus on protein production and crystallisation, solving protein-ligand structures, fragment
-
becomes essential. This project will focus on building a comprehensive digital twin of a future quantum computer to investigate how classical subsystems scale and interact, and how this scaling impacts
-
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
-
must hold, or be close to completion of a doctoral degree in a relevant field (e.g., data science, geography, environmental science, public health, economics). You will have experience relevant for food
-
their career development to establish research independence. For informal enquiries about the position, please contact Prof. Keith Channon: keith.channon@cardiov.ox.ac.uk For more information about working at
-
or your viva has been held. Informal enquiries may be addressed to Prof. Tan (email: jin-chong.tan@eng.ox.ac.uk) For more information about working at the Department, see www.eng.ox.ac.uk/about/work-with-us
-
human tumour models including organ/tumour perfusion, slice culture and organoids to ensure data is clinically relevant and to inspire the next generation of effective treatments. The post would suit
-
specialist knowledge in a relevant subject area. With knowledge of statistics and ability to use statistical packages for analysing data, you will have excellent communication skills and the ability to work co
-
specialist knowledge in a relevant subject area. With knowledge of statistics and ability to use statistical packages for analysing data, you will have excellent communication skills and the ability to work co
-
into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data