<html><head><meta http-equiv="Content-Type" content="text/html; charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class=""><div dir="auto" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class=""><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div class=""><b class=""><br class=""></b></div><div class=""><b class=""><br class=""></b></div><div class=""><b class="">We are excited to announce that the application for Oxford Machine Learning Summer School 2020 is now open</b></div><div class="">Location: Oxford Saïd Business School Oxford (UK)</div><div class="">Date: August 17-22 2020</div><div class="">Application deadline: April 2020</div><div class="">Website: <a href="https://www.oxfordml.school/" class="">www.oxfordml.school</a></div><div class=""><br class=""></div><div class=""><br class=""></div><div class=""><b class="">The OxML.2020 Summer School</b></div><div class="">Oxford Machine Learning Summer School (<a href="http://oxfordml.school/" class="">OxML 2020</a>) will be held at Said Business School (SBS), The University of Oxford (17-22 Aug 2020). The school aims to provide the participants with the best-in-class training on a broad range of advanced topics and developments in machine learning (ML) — including, deep learning (DL). It covers the core ML developments in domains such as Computer Vision and NLP, as well as topics such as Bayesian ML (incl. Gaussian Processes and DBNNs), Causal Inference in ML, Topological approaches in ML, Representation Learning, Transfer Learning, Reinforcement Learning, and Interpretability in ML — just to name a few — that the field is showing a growing interest in. </div><div class=""><br class=""></div><div class="">There will also be a special focus on medicine (the UN’s sustainable development goal #3) through a range of applied talks at the interface of machine learning and healthcare/biomedical sciences (e.g., medical imaging, genetics, bio(medical) informatics, drug discovery, and learning from multi-modal medical data).</div><div class=""><br class=""></div><div class=""><b class="">The Organisers</b></div><div class="">This school is organised by <a href="http://globalgoals.ai/" class="">AI for Global Goals</a>, <a href="http://cifar.ca/" class="">CIFAR</a>, and Oxford University’s <a href="http://sbs.ox.ac.uk/" class="">Saïd Business School</a> and <a href="http://deepmedicine.medsci.ox.ac.uk/" class="">Deep Medicine Program</a>.</div><div class=""><br class=""></div><div class=""><b class="">The Speakers</b></div><div class="">The school’s world-renowned speakers are from Oxford, Cambridge, Stanford, CIFAR, Amazon, DeepMind, Microsoft Research, Prowler, 23andMe, and Arm – just to name a few. The speakers’ bios and more details on their talks will be announced in the coming weeks (you can follow the updates via the <a href="https://www.oxfordml.school/speakers" class="">school’s website</a> and <a href="https://twitter.com/GlobalGoalsAI" class="">Twitter</a> handle).</div><div class=""><br class=""></div><div class=""><b class="">Target audience </b></div><div class="">The school aims to accept up to 100 participants (postgraduate students, as well as researchers and engineers in both academia and industry). The school is primarily designed for those with strong technical backgrounds (through studying and/or working in ML, CS, Stats, Engineering, Biomedical informatics, etc.) who are interested in broadening their ML knowledge beyond their current focus area. </div><div class=""><br class=""></div><div class=""><b class="">Application </b></div><div class="">The application deadline is 30 April 2020; those interested can apply through the <a href="https://forms.gle/TNjoVDmVuR1nAzQF8" class="">application page</a> (or via clicking on the application link at the top-right corner of the website). </div><div class="">All applicants are subject to a selection process.</div><div class="">Note that the application portal may close earlier than the deadline if the number of applications exceeds our capacity to review.</div><div class="">There is no application fee. However for the accepted applicants there will be a registration fee (please read the <a href="https://www.oxfordml.school/faq" class="">Frequently Asked Questions</a> (FAQ) section for more details). The registration fee will allow access to all lectures, lunch, and coffee/refreshments every day, plus the formal dinners that the school will host at Oxford University colleges.</div><div class=""><br class=""></div><div class=""><b class="">Contacting Us </b></div><div class="">For any queries, you can contact us using this email address: <a href="mailto:contact@globalgoals.ai" class="">contact@globalgoals.ai</a></div><div class="">Of course, more information (and possible the answers to some of the questions) can be found on the FAQ section of the website.</div><div class=""><br class=""></div></div>Best,<br class=""><div class=""><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;">—<br class="">Reza Khorshidi, D.Phil. (Oxon)<br class="">Investigator, Machine Learning and Medicine <br class="">DeepMedicine Program, Oxford Martin School<br class="">34 Broad St, Oxford OX1 3BD</div><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><br class=""></div><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><br class=""></div><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><br class=""></div></div></div></div></div></body></html>