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Position: Research Fellow (Training Fellow in Theoretical Neuroscience or Machine Learning)
Institution: University College London
Department: UCL Gatsby Computational Neuroscience Unit
Location: London, United Kingdom
Duties: The Gatsby Computational Neuroscience Unit invites applications for postdoctoral training fellowships. Funded by the Gatsby Foundation, the Unit is a world-leading centre for research in theoretical neuroscience and machine learning and related areas; The successful applicants will carry out original research in theoretical neuroscience or machine learning under the guidance of a member of faculty. Primary projects will align with the current themes of research listed below, with scope for further independent projects where mutually agreed to be of value for the Fellows training and career development; Research themes (and associated faculty mentors) for which Training Fellowships are currently available are: Generative models (implicit, energy-based, flows...), causal modelling (e.g. detecting and correcting for hidden confounders), nonparametric hypothesis testing (Arthur Gretton); Algorithms and mechanisms of inference and planning under uncertainty in neural systems (Maneesh Sahani); Statistical and machine-learning approaches to analysis and interpretation of population neural data (Maneesh Sahani); Learning and inference in neural systems, using normative, typically Bayesian, approaches, but also making use of recent advances in Deep Learning (Peter Latham); Bayesian non-parametric methods, Bayesian inference, variational inference (Peter Orbanz); Network analysis. This involves a range of problems and methods: Network models and learning algorithms, random graphs, mathematical statistics of dependent random variables, and applications of probabilistic symmetries in machine learning and statistics (Peter Orbanz); Research Fellows will be responsible for the primary execution of research projects (with opportunities for co-supervision of students), presentation of results at conferences and seminars, and publication in suitable media; Collaboration within and outside the Unit is actively encouraged and supported through the provision of a generous annual travel allowance; To ensure the intellectual renewal of the unit, training fellowships are not funded by the Foundation beyond a maximum three year period
Requirements: Candidates will be required to demonstrate a strong quantitative background in theoretical neuroscience, machine learning, statistics, computer science, physics or engineering; a record of publication in highly respected journals and conferences; and must hold a PhD in a relevant field by the agreed start date of the position
   
Text: Research Fellow (Training Fellow in Theoretical Neuroscience or Machine Learning), - Ref:1869124 Click here to go back to search results Apply Now UCL Department / Division UCL Gatsby Computational Neuroscience Unit Location of position London Grade 7 Hours Full Time Salary (inclusive of London allowance) £35,965 - £43,470 per annum Duties and Responsibilities The Gatsby Computational Neuroscience Unit invites applications for postdoctoral training fellowships. Funded by the Gatsby Foundation, the Unit is a world-leading centre for research in theoretical neuroscience and machine learning and related areas. For details of our research please see http://www.gatsby.ucl.ac.uk/research.html. The successful applicants will carry out original research in theoretical neuroscience or machine learning under the guidance of a member of faculty. Primary projects will align with the current themes of research listed below, with scope for further independent projects where mutually agreed to be of value for the Fellows training and career development. Research themes (and associated faculty mentors) for which Training Fellowships are currently available are: Generative models (implicit, energy-based, flows...), causal modelling (e.g. detecting and correcting for hidden confounders), nonparametric hypothesis testing (Arthur Gretton) Algorithms and mechanisms of inference and planning under uncertainty in neural systems (Maneesh Sahani). Statistical and machine-learning approaches to analysis and interpretation of population neural data (Maneesh Sahani). Learning and inference in neural systems, using normative, typically Bayesian, approaches, but also making use of recent advances in Deep Learning (Peter Latham). Bayesian non-parametric methods, Bayesian inference, variational inference (Peter Orbanz). Network analysis. This involves a range of problems and methods: Network models and learning algorithms, random graphs, mathematical statistics of dependent random variables, and applications of probabilistic symmetries in machine learning and statistics (Peter Orbanz). Research Fellows will be responsible for the primary execution of research projects (with opportunities for co-supervision of students), presentation of results at conferences and seminars, and publication in suitable media. Collaboration within and outside the Unit is actively encouraged and supported through the provision of a generous annual travel allowance. To ensure the intellectual renewal of the unit, training fellowships are not funded by the Foundation beyond a maximum three year period. The post is funded for two years in the first instance. Key Requirements Candidates will be required to demonstrate a strong quantitative background in theoretical neuroscience, machine learning, statistics, computer science, physics or engineering; a record of publication in highly respected journals and conferences; and must hold a PhD in a relevant field by the agreed start date of the position. Further Details A job description and person specification can be accessed at the bottom of this page. To apply for the vacancy please click on the Apply Now button below. Academic enquiries should be directed to the appropriate faculty mentor, Prof.Arthur Gretton (a.gretton@gmail.com), Prof. Peter Latham (pel@gatsby.ucl.ac.uk) or Dr. Peter Orbanz (p.orbanz@ucl.ac.uk) or Prof. Maneesh Sahani (maneesh@gatsby.ucl.ac.uk) For queries regarding the application process, please contact Mike Sainsbury, (m.sainsbury@ucl.ac.uk). Please be sure to attach to your online application a copy of your CV, statement of research interests, clearly specifying the research theme(s) and faculty mentor(s) of interest (and highlighting relevant experience), and full contact details (including e-mail addresses) for three academic referees. CVs should include: education history, details of current or most recent position and details of previous employment including any career breaks or fellowships. UCL Taking Action for Equality We will consider applications to work on a part-time, flexible and job share basis wherever possible. Closing Date 16 Aug 2020 Latest time for the submission of applications 23:59 Interview date TBC Our department is working towards an Athena SWAN award. We are committed to advancing gender equality within our department. This appointment is subject to UCL Terms and Conditions of Service for Research and Support Staff. Please use these links to find out more about UCL working life including the benefits we offer and UCL Terms and Conditions related to this job. Job Description and Person Specification Apply Now
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