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Computational and Biological Learning Lab
https://cbl.eng.cam.ac.uk/4 Jul 2024: Research includes Bayesian learning, computational neuroscience, statistical machine learning and sensorimotor control. ... Kris is now Dr Kris! He successfully defended his thesis entitled “Strong and weak principles of Bayesian machine learning for -
New faculty member Richard Turner | Cambridge Machine Learning Group
https://mlg.eng.cam.ac.uk/news/new-faculty-member-richard-turner/3 Jul 2024: His research programme spans computer perception, signal processing, machine learning, and neuroscience. ... He’ll strengthen connections between the Computational and Biological Learning Lab, the Machine Intelligence Lab and the Signal Processing Lab. -
Professor Neil Lawrence | Queens' College
https://www.queens.cam.ac.uk/professor-neil-lawrence5 Jul 2024: Professor Neil Lawrence. Professor Neil Lawrence. Professorial Fellow. DeepMind Professor of Machine Learning at the University of Cambridge. ... Previous positions include: Director of Machine Learning for Amazon in Cambridge, Professor in Computational -
Sectors: Data science | Careers Service
https://www.careers.cam.ac.uk/sectors-data-science7 Jul 2024: Disciplines that are attractive to data science recruiters include physics, astronomy, astrophysics, physical chemistry, computational biology, neuroscience, mathematics, statistics, engineering, machine learning, operations research, economics, -
http://www.jobs.cam.ac.uk/job/?unit=u10055&format=rss | School of …
https://www.bio.cam.ac.uk/aggregator/sources/207 Jul 2024: You will receive multi-disciplinary research training at the interface of machine learning, neuroscience, and clinical translation. ... A strong academic track record and programming skills are essential. Experience with machine learning, data science, -
Computational and Biological Learning Lab
https://cbl.eng.cam.ac.uk/people/zg201/4 Jul 2024: He was co-founder of Geometric Intelligence (now Uber AI Labs) and advises a number of AI and machine learning companies. ... His academic career includes concurrent appointments as one of the founding members of the Gatsby Computational Neuroscience -
Zoubin Ghahramani | Department of Engineering
https://www.eng.cam.ac.uk/profiles/zg201My work focuses on advancing the general mathematical and algorithmic foundations of these fields, although I have also worked on applications of Bayesian machine learning to computational biology and bioinformatics, econometrics ... His academic career -
https://mlg.eng.cam.ac.uk/index.xml
https://mlg.eng.cam.ac.uk/index.xml3 Jul 2024: We encourage applications from outstanding candidates with academic backgrounds in Mathematics, Physics, Computer Science, Engineering and related fields, and a keen interest in doing basic research in machine learning and its ... in Machine Learning, -
Topic 6 - Computational Neurosciences | Cambridge Centre for…
https://ftd.neurology.cam.ac.uk/research/compneurosci23 Feb 2024: Topic 6 - Computational Neurosciences. Computational Neuroscience - from Neuron to Behaviour. ... We also use computational neurosciences approaches such as mathematical modelling and machine learning in order to understand behaviour such as decision -
Dr Richard Turner honoured with teaching award | Department of…
https://www.eng.cam.ac.uk/news/dr-richard-turner-honoured-teaching-awardRichard, who works as a lecturer in the Computational and Biological Learning Lab, won in the Lecturer category for his classes on software engineering, computer vision, machine learning and neuroscience. ... He earned his PhD in computational -
Prof Sir Mackay
www.tcm.phy.cam.ac.uk/profiles/djcm1/31 Dec 2015: During my PhD (at Caltech, 1988-1991) I worked on Bayesian methods for neural networks and other machine learning methods, and on computational neuroscience (for example, simple models of neural development). ... I wrote up the connections between -
Member: Onno Kampman - Cambridge Neuroscience
https://neuroscience.cam.ac.uk/member/opk20/Department. Research ThemeResearch Focus Keywords. Machine Learning. Bayesian Inference. fMRI. Functional Connectivity. ... Dr Onno Kampman. University Position. PhD student. Visiting Scientist. Interests. Computational neuroscience, using machine -
Professor Richard Turner | Cambridge Centre for Data-Driven Discovery
https://www.c2d3.cam.ac.uk/directory/422/professor-richard-turnerHe then studied for his PhD in Computational Neuroscience and Machine Learning at the Gatsby Computational Neuroscience Unit, UCL. ... He now holds a Readership in the Machine Learning Group which is part of the Computational and Biological Learning Lab -
Professor David Barrett | Cambridge Centre for Data-Driven Discovery
https://www.c2d3.cam.ac.uk/directory/386/professor-david-barrettComputational and Biological Learning,. Office BE-435,. Information Engineering Division,, Department of Engineering,, University of Cambridge. ... I completed a Ph.D in Computational Neuroscience and Machine Learning at the Gatsby Unit, UCL, with Prof. -
Member: Tobias Goehring - Cambridge Neuroscience
https://neuroscience.cam.ac.uk/member/tobiasgoehring/I combine techniques from Psychology, Engineering, Auditory Neuroscience and Machine Learning to improve Medical Hearing Devices such as Cochlear Implants and Hearing Aids. ... Auditory inspired machine learning techniques can improve speech -
Learning more Python at CUED
https://help.eng.cam.ac.uk/cued-python/learning-more-python-at-cued/3rd year – Various Easter Term projects (4 weeks) involve programming – “CT Reconstruction and Visualisation”, “Image Processing”, “Machine Learning” (Python), “Data Analysis”, “Software” (Python), etc. ... Several modules also -
Sectors: Data science | Careers Service
https://www.careers.cam.ac.uk/sectors-data-science8 Oct 2020: Disciplines that are attractive to data science recruiters include physics, astronomy, astrophysics, physical chemistry, computational biology, neuroscience, mathematics, statistics, engineering, machine learning, operations research, economics, -
1 Set Unit Title Mode IIBM1 4A2 Computational Fluid ...
https://teaching.eng.cam.ac.uk/download/file/5782IIBL4 4G3 Computational Neuroscience cIIBL2 4G4 Biomimetics cIIBM6 4G5 Materials and Molecules: Modelling, Simulation and Machine Learning cIIBM1 4G6 Cellular and Molecular Biomechanics pIIBL11 4G9 Biomedical Engineering c. ... 4A7 Aircraft Aerodynamics -
Notices by Faculty Boards, etc. - Cambridge University Reporter 6744
https://www.reporter.admin.cam.ac.uk/reporter/2023-24/weekly/6744/section4.shtml5 Jun 2024: 4G3. Computational neuroscience. c. 4G5. Materials and molecules: Modelling, simulation and machine learning. ... Electricity and environment (TPE22). c. 4M24. Computational statistics and machine learning. -
IIB M&S 2023-24.V4 (for publication)
https://teaching.eng.cam.ac.uk/download/file/6501IIBM11 4M22 Climate Change Mitigation c. IIBL6 4M23 Electricity and Environment (TPE22) cIIBM8 4M24 Computational Statistics and Machine Learning pcIIBL3 4M26 Algorithms and Data Structures p. ... IIB Sets Michaelmas Term 20224A2 Computational Fluid -
IIB M&S 2023-24.V4 (for publication)
https://teaching.eng.cam.ac.uk/download/file/6146IIBM11 4M22 Climate Change Mitigation c. IIBL6 4M23 Electricity and Environment (TPE22) cIIBM8 4M24 Computational Statistics and Machine Learning pcIIBL3 4M26 Algorithms and Data Structures p. ... IIB Sets Michaelmas Term 20224A2 Computational Fluid -
Notes: Set Unit Title Mode Notes IIBM1 4A2 Computational ...
https://teaching.eng.cam.ac.uk/download/file/6608IIBL4 4G3 Computational Neuroscience c. IIBL8 4G5 Materials and Molecules: Modelling, Simulation and Machine Learning c. ... 4A7 Aircraft Aerodynamics and Design c4C3 Advanced Functional Materials and Devices p4D5 Deep Foundations and Underground -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2023-24 …
https://teaching.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2023-24describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in -
Computational and Biological Learning Lab
https://cbl.eng.cam.ac.uk/vacancies/blg-phd/4 Jul 2024: Students in computational neuroscience benefit from the strong machine learning group within CBL. ... Students seeking to combine work in neuroscience and machine learning are particularly encouraged to apply. -
Research Assistants | Cambridge Centre for Neuropsychiatric Research
https://ccnr.ceb.cam.ac.uk/Team/Research-Assistants7 Jul 2024: During my studies there, I developed strong skills in applied data science and machine learning, as well as fundamental knowledge of neural computation and computational cognitive neuroscience, focused on realistic simulation ... health. Contact: -
Edoardo Chidichimo | Department of Psychology
https://www.psychol.cam.ac.uk/staff/edoardo-chidichimo7 Jul 2024: In the future, Edoardo hopes to combine computational approaches (e.g., machine learning and social network analyses) to anthropologically- and ethnographically-derived hypotheses in order to better predict and prevent violent ... Interdisciplinarity; -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2020-21 …
https://teaching.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2020-21describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2022-23 …
https://teaching.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2022-23describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2021-22 …
https://teaching.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2021-22describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in -
Computational and Biological Learning Laboratory | Department of…
https://www.eng.cam.ac.uk/research/academic-divisions/information-engineering/research-groups/computational-and-biologicalComputational and Biological Learning Laboratory. The Computational and Biological Learning Laboratory uses engineering approaches to understand the brain and to develop artificial learning systems. ... Research includes Bayesian learning, computational -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2019-20 …
https://teaching.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2019-20describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2018-19 …
https://teaching.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2018-19describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2017-18 …
https://teaching.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2017-18describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in -
Computational Learning and Memory Group
https://cbl.eng.cam.ac.uk/lengyel/vacancies/blg-phd/4 Jul 2024: Students in computational neuroscience benefit from the strong machine learning group within CBL. ... Students seeking to combine work in neuroscience and machine learning are particularly encouraged to apply. -
Neural Sensory Processing Group
https://cbl.eng.cam.ac.uk/ahmadian/vacancies/blg-phd/4 Jul 2024: Students in computational neuroscience benefit from the strong machine learning group within CBL. ... Students seeking to combine work in neuroscience and machine learning are particularly encouraged to apply. -
Neural Dynamics and Control Group
https://cbl.eng.cam.ac.uk/hennequin/vacancies/blg-phd/4 Jul 2024: Students in computational neuroscience benefit from the strong machine learning group within CBL. ... Students seeking to combine work in neuroscience and machine learning are particularly encouraged to apply. -
paper8-lect0-13
https://mlg.eng.cam.ac.uk/zoubin/p8-07/lect0.pdf27 Jan 2023: Why is this useful? Machine Learning Machine learning is an interdisciplinary field focusing on both the mathematical foundations and practical applications of systems that learn, reason and act. • ... How does it fit into Information Engineering? • -
Andrew Wilson wins Best Student Paper Award at the Uncertainty in…
https://www.eng.cam.ac.uk/news/andrew-wilson-wins-best-student-paper-award-uncertainty-artificial-intelligence-conferenceAndrew Wilson is in his second year of a PhD in machine learning, in the Computational and Biological Learning Group. ... Machine learning is partly inspired by advances in neuroscience, and is focused on developing algorithms for learning and decision -
Jonathan So - 2019 Cohort | Harding Distinguished Postgraduate…
https://www.hardingscholars.fund.cam.ac.uk/jonathan-so-2019-cohort15 Oct 2019: Research interests . 1. Probabilistic machine learning. 2. Computational neuroscience. In my doctoral research I will investigate how we can learn useful probabilistic representations from data in a fully unsupervised manner, given ... machine learning -
Cambridge University Reporter Special
https://www.reporter.admin.cam.ac.uk/reporter/2005-06/weekly/6023/9.html28 Jan 2022: Information Engineering at Cambridge spans the broad areas of control, communications, signal, speech, image and vision processing, machine learning, and computational neuroscience. ... the cellular basis of learning and memory, control of neuronal -
Cognitive Systems Engineering @ Cambridge University
https://mlg.eng.cam.ac.uk/cogsys/27 Jan 2023: communications. computational neuroscience. computer vision and image processing. machine learning. speech recognition, machine translation and dialog systems. ... Current research interests include Bayesian approaches to machine learning, artificial -
Engineering Tripos, Part IIB: Notice concerning Engineering Areas |…
https://teaching.eng.cam.ac.uk/content/engineering-tripos-part-iib-notice-concerning-engineering-areas4M22. Climate Change Mitigation. 4M23. Electricity and Environment (TPE22). 4M24. Computational Statistics and Machine Learning. ... 4G3. Computational Neuroscience. 4G5. Materials and Molecules: Modelling, Simulation and Machine Learning. -
Zoubin Ghahramani Bio
https://mlg.eng.cam.ac.uk/zoubin/bio.html27 Jan 2023: He was co-founder of Geometric Intelligence (now Uber AI Labs) and advises a number of AI and machine learning companies. ... His academic career includes concurrent appointments as one of the founding members of the Gatsby Computational Neuroscience -
CEB-MPhil Biotechnology
https://www.ceb.cam.ac.uk/study/grad/mphil/biotech7 Jul 2024: Computational neuroscience (Department of Engineering). This course covers basic topics in computational neuroscience and demonstrates how mathematical analysis and ideas from dynamical systems, machine learning, optimal control and probabilistic -
https://mlg.eng.cam.ac.uk/news/index.xml
https://mlg.eng.cam.ac.uk/news/index.xml3 Jul 2024: group. David was a terrific researcher and teacher in machine learning, and a passionate campaigner for social good through his work on energy. ... The post-holder will be a member of both CFI, and the Machine Learning Group, run by Prof Zoubin Ghahramani -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2022-23 …
https://teaching22-23.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2022-23describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2021-22 …
https://teaching22-23.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2021-22describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2020-21 …
https://teaching22-23.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2020-21describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2018-19 …
https://teaching22-23.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2018-19describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2019-20 …
https://teaching22-23.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2019-20describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in
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