366 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at University of Oxford
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
interdisciplinary research has synergies with many of the department's research priorities, including exoplanet studies, machine learning, cutting-edge radio instrumentation and digital signal processing, citizen
-
fundamental research, we create widely used open-source software including autodE, cgbind/C3, and mlp-train. Our recent advances in Machine Learning Interatomic Potentials (MLIPs) form the foundation of our ERC
-
that integrate multi-omics data to uncover mechanisms of disease, cellular resilience, and therapeutic response. The post holder will lead research applying large-scale machine learning and foundation models
-
: Earth Sciences, Bioscience, Interdisciplinary Life and Environmental Science, Inorganic Materials for Advanced Manufacturing, Chemical Synthesis for a Healthy Planet,Statistics and Statistical Machine
-
open-source software, including autodE, cgbind/C3, and mlp-train, and are pioneering new frameworks for training Machine Learning Interatomic Potentials (MLIPs). We are seeking a highly motivated
-
Internal candidates will be given priority for this recruitment and must apply via the Employee Dashboard. About the Role The Oxford Applied and Theoretical Machine Learning group at the Department
-
application of AI and machine learning models to interpret complex X-ray datasets, and the integration of experimental and computational insights to generate actionable knowledge that advances sustainable metal
-
The postdoctoral researcher will lead the development of computational methods for aligning cortical organisation across species using transcriptomic and anatomical data combined with modern machine
-
and advanced machine learning approaches to identify novel imaging markers of mental health disorders and cognitive function; 2) developing robust MRI-based acquisition, image reconstruction and
-
imaging datasets and advanced machine learning approaches to identify novel imaging markers of mental health disorders and cognitive function; 2) developing robust MRI-based acquisition, image