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Position: PhD Project in Geometric Machine Learning
Institution: Technical University of Denmark
Location: Kongens Lyngby, Lyngby‐Taarbæk Municipality, Denmark
Duties: The PhD project revolve around the goal of learning operational representations, i.e. representations that are naturally equipped with a set of well-defined operations that may be performed. For example, we may seek a representation that supports operators akin to addition and subtraction, or we may seek a representation that naturally supports integration (in order to assign probabilities to events). In practice, the project will focus on building both practical tools as well as theoretical foundations for working with random Riemannian representations, which naturally appear in many generative models. For more details see Operational Representation Learning
Requirements: Candidates should have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. The master degree should be in computational science and engineering (CSE), applied mathematics, or engineering, or equivalent academic qualifications; Preference will be given to candidates who can document experience with machine learning, and in addition have an interest in basic research. Experience with Riemannian geometry is a benefit, but not a requirement. Furthermore, good command of the English language is essential
   
Text: PhD Project in Geometric Machine Learning DTU Compute Share on Facebook Share on Twitter Share on Linkedin Tuesday 05 Nov 19 Apply for this job Apply no later than 3 January 2020 Apply for the job at DTU Compute by completing the following form. Apply online DTU Compute’s Section for Cognitive Systems, would like to invite applications for a 3-year PhD position starting March 2020. The project is financed by the European Research Council, through a Starting Grant. The Section for Cognitive Systems is an internationally renowned group for machine learning research. The group aims for the highest quality research. You are encouraged to collaborate both within the group and with other international groups. We emphasize a healthy work/life balance based on the premise that you do the best work when you are happy. Project Description The PhD project revolve around the goal of learning operational representations, i.e. representations that are naturally equipped with a set of well-defined operations that may be performed. For example, we may seek a representation that supports operators akin to addition and subtraction, or we may seek a representation that naturally supports integration (in order to assign probabilities to events). In practice, the project will focus on building both practical tools as well as theoretical foundations for working with random Riemannian representations, which naturally appear in many generative models. For more details see Operational Representation Learning . Most learned representations are treated as being Euclidean even if it is trivial to construct counter-examples showing that the Euclidean assumption lead to arbitrariness. You will join a team of people dedicated to avoiding this arbitrariness. You will work with nonlinear generative models and use geometric techniques to develop well-defined operations that can be meaningfully applied in the representation space of the model. The end-goal is to both improve the modelling capacity of generative models, but also to improve their general interpretability. Depending on interest and qualifications of the applicant, the project can either be theoretical, applied, or a combination thereof. We generally believe that theory and applications must go hand in hand to ensure that the theory is meaningful and beneficial to scientific discovery. More details are available at Open positions . Qualifications Candidates should have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. The master degree should be in computational science and engineering (CSE), applied mathematics, or engineering, or equivalent academic qualifications. Preference will be given to candidates who can document experience with machine learning, and in addition have an interest in basic research. Experience with Riemannian geometry is a benefit, but not a requirement. Furthermore, good command of the English language is essential. Approval and Enrolment The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in the DTU Compute PhD School Programme. For information about the general requirements for enrolment and the general planning of the PhD study programme, please see the DTU PhD Guide . Assessment The assessment of the applicants will be made by Associate professor Søren Hauberg. We offer DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility. Salary and appointment terms The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The position is a full-time position. The period of employment is 3 years starting March 2020 (or as soon as possible thereafter). You can read more about career paths at DTU here . Further Information Further information concerning the project can be obtained from Associate professor Søren Hauberg, sohau@dtu.dk . Further information concerning the application is available at the DTU Compute PhD homepage . Application Please submit your online application no later than 3 January 2020 (local time) . Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file . The file must include: A letter motivating the application (cover letter) Curriculum vitae Grade transcripts and BSc/MSc diploma Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here ) Candidates may apply prior to obtaining their master's degree, but cannot begin before having received it. Applications and enclosures received after the deadline will not be considered. All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply. DTU Compute is an internationally unique academic environment spanning the science disciplines mathematics, statistics and computer science. At the same time we are an engineering department covering informatics and communication technologies (ICT) in their broadest sense. Finally, we play a major role in addressing the societal challenges of the digital society where ICT is a part of every industry, service, and human endeavour. DTU Compute has a total staff of 400 including 100 faculty members and 130 Ph.D. students. We offer introductory courses to all engineering programmes at DTU and specialised courses to the mathematics, computer science, and other programmes. We offer continuing education courses and scientific advice within our research disciplines, and provide a portfolio of innovation activities for students and employees. Technology for people DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 11,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. Our main campus is in Kgs. Lyngby north of Copenhagen and we have campuses in Roskilde and Ballerup.
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