Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
Your profile PhD applicants must possess a Master's degree in mathematics, theoretical physics, or computer science. Candidates should have an exceptional academic record and a robust mathematical foundation. Candidates are also expected to have strong coding and implementation skills, with the...
-
applications, including solving mathematical reasoning problems and tackling the Abstraction and Reasoning Corpus (ARC) challenge among others. The ideal candidate has a strong background in machine learning and
-
overuse injuries. Wearable sensors to quantify of the impact and benefit of sleep on the recovery, performance and overall wellbeing of athletes. Using big data and machine learning methods to identify
-
Experience and practical knowledge of programming languages and tools (e.g. Python, Java, etc.) Knowledge in Software Engineering, AI, machine learning is an advantage Experience with software observability
-
to optimise built-environment thermodynamics and occupant comfort by creating predictive AI tools for spatiotemporal heat transfer. Machine learning algorithms will identify energy inefficiencies and propose
-
learning and machine learning for biological data Sequence and structure analysis of large-scale datasets Functional annotation and evolutionary analysis Collaborative research with experimental virology
-
, into the research groups of Prof. Oliver Buxton whose expertise is on turbulence, wind-energy flows, and turbulent cloud microphysics and Prof. Luca Magri whose expertise is in scientific machine learning
-
processing, embedded systems, machine learning, and networked communication. Each PhD position corresponds to a dedicated research topic within the consortium. All doctoral researchers will benefit from joint
-
analysis across case study regions. The successful candidate will work on the development and application of AI/Machine learning and behavioural modelling within the North and Baltic seas, utilising legacy
-
at conferences. You will work at the interface between AI, chemistry, and biology, with a proactive and interdisciplinary attitude. You will become a member of the Molecular Machine Learning team (led by Prof. F