Sort by
Refine Your Search
-
of original machine-learning based algorithms and models for multi-modal ultrasound guidance that are intuitive for a non-specialist to use while scanning and trustworthy. You will work with clinical domain
-
Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods
-
sleep; performing anatomical tract tracing; analysing existing and new datasets using python and Matlab using advanced statistical methods such as machine learning; collaborating with other members
-
learning, at the intersection of reinforcement learning, deep learning and computer vision, in order to train effective robotic agents in simulation. You should hold a relevant PhD/DPhil (or near completion
-
projects in computer vision research, with a particular emphasis on Spatial Intelligence, 3D Computer Vision, and 3D Generative AI. You should hold a relevant PhD/DPhil (or near completion*) in Computer
-
PhD in Chemistry or a relevant subject area, (or be close to completion) prior to taking up the appointment. The research requires experience in computational chemistry, including machine learning
-
evaluations, attacks on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related
-
a PhD/DPhil or equivalent in a quantitative discipline such as computer science, statistics, machine learning, statistical or population genetics, or a related field. They should have experience in
-
We are seeking a full-time Postdoctoral Research Associate in Machine Learning for Grid-Edge Flexibility to join the Power Systems Architecture Lab within the Department of Engineering Science
-
learning (IRL) techniques. You should have a relevant PhD/DPhil (or be near completion), together with research experience in inverse reinforcement learning (or related machine learning techniques