Graphical Models
Graphical Models
Gatsby Computational Neuroscience Unit
4-Year PhD Programme in Theoretical Neuroscience and Machine Learning Call for Applications! Deadline: 13 November 2022 The Gatsby Computational Neuroscience Unit is a leading research centre focused on theoretical neuroscience and machine learning. We study (un)supervised and reinforcement learning; inference, coding and neural dynamics; Bayesian and kernel methods; deep learning; with applications to the analysis of perceptual processing and cognition, neural data, signal and image processing, machine vision, network data and nonparametric hypothesis testing. The unit provides a unique opportunity for a critical mass of theoreticians to interact closely with one another and with researchers at the Sainsbury Wellcome Centre for Neural Circuits and Behaviour (SWC), the Centre for Computational Statistics and Machine Learning (CSML) and related UCL departments such as Computer Science; Statistical Science; Artificial Intelligence; the ELLIS Unit at UCL; Neuroscience; and the nearby Alan Turing and Francis Crick Institutes. Our PhD programme provides a rigorous preparation for a research career. Students complete a 4-year PhD in either machine learning or theoretical and computational neuroscience, with minor emphasis in the complementary field. Courses in the first year provide a comprehensive introduction to both fields and systems neuroscience. Students are encouraged to work and interact closely with SWC/CSML researchers to take advantage of this uniquely multidisciplinary research environment. Full funding is available regardless of nationality. The unit also welcomes applicants who have secured or are seeking funding from other sources. To apply, please visit www.ucl.ac.uk/gatsby/study-and-work/phd-programme
Prof. Dr.-Ing. Marcus Magnor
The job is a W3 Full Professorship for Artificial Intelligence in interactive Systems at Technische Universität Braunschweig. The role involves expanding the research area of data-driven methods for interactive and intelligent systems at the TU Braunschweig and strengthening the focal points 'Data Science' and 'Reliability' of the Department of Computer Science. The position holder is expected to have a strong background in Computer Science with a focus on Artificial Intelligence/Machine Learning, specifically in the areas of Dependable AI and Explainable AI. The role also involves teaching, topic-related courses in the areas of Artificial Intelligence and Machine Learning to complement the Bachelor's and Master's degree programs of the Department of Computer Science.
Prof. Dr.-Ing. Marcus Magnor
The position holder has a strong background in Computer Science with a focus on Artificial Intelligence/Machine Learning, specifically in the areas of Dependable AI and Explainable AI. Applicants should possess a method-oriented research focus on machine learning and have made internationally recognized contributions to at least one of the current research areas such as neural networks, generative and adversarial models, online and transfer learning, federated learning, (deep) reinforcement learning, probabilistic inference, graphical models, and/or MDP/POMDP. A researcher is sought who is able to combine the theoretical-methodological investigation and development of learning methods with applications in interactive intelligent systems, for example in autonomous robots, intelligent virtual agents, or intelligent networked production systems. Suitable applicants are expected to show an active interest in the concrete implementation of cognitive abilities in technical systems, ensuring compatibility with partners in engineering and natural sciences. With his/her research performance, the position holder will enhance the international visibility of TU Braunschweig in the field of Artificial Intelligence. In teaching, topic-related courses in the areas of Artificial Intelligence and Machine Learning shall complement the Bachelor's and Master's degree programs of the Department of Computer Science. In particular, the topic of Machine Learning/Artificial Intelligence is to be anchored in undergraduate teaching with a new compulsory Bachelor course. Participation in the academic self-administration of the university is expected as well as the willingness to actively shape computer science at the TU Braunschweig.
Prof. Dr.-Ing. Marcus Magnor
The Technische Universität Braunschweig is offering a W3 Full Professorship for Artificial Intelligence in interactive Systems. The position holder is expected to have a strong background in Computer Science with a focus on Artificial Intelligence/Machine Learning, specifically in the areas of Dependable AI and Explainable AI. The researcher is expected to combine the theoretical-methodological investigation and development of learning methods with applications in interactive intelligent systems. In teaching, topic-related courses in the areas of Artificial Intelligence and Machine Learning shall complement the Bachelor's and Master's degree programs of the Department of Computer Science. Participation in the academic self-administration of the university is expected as well as the willingness to actively shape computer science at the TU Braunschweig.