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Position: Head Research Engineer - Machine Learning and Neural Data
Institution: University College London
Department: Gatsby Computational Neuroscience Unit
Location: London, United Kingdom
Duties: Members of the Gatsby Computational Neuroscience Unit (GCNU) have made many key contributions to the development of machine learning, statistics and neural data analysis over the past two decades. This means we now have a unique opportunity for a Head Research Engineer to lead and develop this work. In the role you will establish a small team to work with academic staff and end-users to design, implement, document and publish these software systems in a way that is suitable for developers seeking to maintain or extend it
Requirements: This is a challenging but exciting role. You will value the opportunity to contribute to the mission of a world-class research environment, and particularly to help make exciting new developments in the field available to a wider audience. You will be expected to have a PhD or equivalent experience following a post-graduate degree in machine learning, statistics, computing, or a related field along with substantial knowledge of and experience with software development best practice. You should have substantial experience with at least one of python/numpy or MATLAB and familiarity with the other; some familiarity with probabilistic machine learning methods and a good working knowledge of linear algebra, statistical methods; and strong analytical and general mathematical skills. The successful candidate will have the ability to lead a small team of research engineers and proven experience of building successful collaborative relationships in a collegiate environment
   
Text: Head Research Engineer - Machine Learning and Neural Data, - Ref:1753472 Click here to go back to search results Apply Now UCL Department / Division Gatsby Computational Neuroscience Unit Location of position London Grade 9 Hours Full Time Salary (inclusive of London allowance) Competitive salary and benefits Duties and Responsibilities The Gatsby Computational Neuroscience Unit (GCNU) at UCL is a world-leading centre for theoretical neuroscience and machine learning research running international PhD and postdoctoral training programmes. Members of the unit have made many key contributions to the development of machine learning, statistics and neural data analysis over the past two decades. We now want to extend our mission by establishing a new team who will translate and adapt novel machine learning and neural data analytic algorithms and technologies developed in the course of our research into robust, scalable, open and useable software applications and platforms that can be used by both our collaborators and a wider audience. This means we now have a unique opportunity for a Head Research Engineer to lead and develop this work. In the role you will establish a small team to work with academic staff and end-users to design, implement, document and publish these software systems in a way that is suitable for developers seeking to maintain or extend it. In line with our mission published code will be open source. In this role you will work with collaborators to understand particular data sets or applications and will have the opportunity to engage and assist with the research and development needed to adapt algorithms to address these cases. A key responsibility will be to facilitate practical interaction between the theoretical and algorithmic work of the Gatsby Unit and the experimental systems neuroscience carried out in our sister institute, the Sainsbury-Wellcome Centre for Neural Circuits and Behaviour (SWC). The Unit is externally funded with funding awarded in five year tranches subject to periodic funder review. Subject to successful grant renewal, staff posts will be extended in line with successive funding periods. The post is funded until 31 July 2021 in the first instance. Key Requirements This is a challenging but exciting role. You will value the opportunity to contribute to the mission of a world-class research environment, and particularly to help make exciting new developments in the field available to a wider audience. You will be expected to have a PhD or equivalent experience following a post-graduate degree in machine learning, statistics, computing, or a related field along with substantial knowledge of and experience with software development best practice. You should have substantial experience with at least one of python/numpy or MATLAB and familiarity with the other; some familiarity with probabilistic machine learning methods and a good working knowledge of linear algebra, statistical methods; and strong analytical and general mathematical skills. The successful candidate will have the ability to lead a small team of research engineers and proven experience of building successful collaborative relationships in a collegiate environment. Further Details We are located in a new purpose-built building close to UCL?s main Gower Street campus in central London. We offer a fully competitive salary along with a full range of UCL staff benefits, including a generous annual leave entitlement, occupational pension scheme and excellent family-friendly policies and staff discounts. A job description and person specification can be accessed below. For informal enquiries please contact Maneesh Sahani, Director GCNU at maneesh@gatsby.ucl.ac.uk To apply for this vacancy please click the "apply now" button below. We particularly welcome female applicants and those from an ethnic minority, as they are under-represented within UCL at this level. We will consider applications to work on a part-time, flexible and job share basis wherever possible. Closing Date 29 Oct 2018 Latest time for the submission of applications 23:59 Interview date TBC 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. Head Research Engineer, GCNU - JD&PS Apply Now
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