The successful applicant will; Analyze and model structures in large scale data, including mobility data collected from mobile phones, and social media data; Collaborate with researchers from both computational and social sciences in a truly interdisciplinary environment; Co-author scientific papers aimed at high-impact journals; Participate in international conferences
You should have a PhD degree or equivalent; You must have a background within physics, applied mathematics, machine learning, computational social science, or related fields; A track record of publishing interesting work within some of those fields; Experience analyzing large-scale datasets in Python; Experience with machine learning (incl) deep learning for prediction problems; Broader experience with programming is an advantage; Experience in time-series analysis is an advantage; Experience with modeling complex networks or human mobility is an advantage
Postdoc in Modeling Societal Impact of COVID-19 DTU Compute Share on Facebook Share on Twitter Share on Linkedin Tuesday 17 Nov 20 Apply for this job Apply no later than 6 December 2020 Apply for the job at DTU Compute by completing the following form. Apply online DTU Compute’s Sections for Cognitive Systems, would like to invite applications for a 2-year postdoc position starting 1 January 2021. The project is financed by the Carlsberg Semper Ardens project HOPE. The researcher will be supervised by Professor Sune Lehmann at the Section for Cognitive Systems, DTU Compute, but also associated with SODAS at the University of Copenhagen. The Cognitive Systems Section at DTU: Advanced data analysis is increasingly a determinant for productivity and personal quality of life. The Section for Cognitive Systems researches information processing in man and computer, with a particular focus on the signals they exchange - audio, imagery, behavior - and the opportunities these signals offer for modeling and prediction. Our research is based on statistical machine learning and signal processing, on quantitative analysis of digital media and text, on mobility and complex networks, and on cognitive psychology. Center for Social Data Science (SODAS) at University of Copenhagen : New types of data, in particular digital data, is flooding the social sciences. The broad catchphrase for the analysis of such data is ‘data science’. The Faculty of Social Sciences has made new, digital forms of data - sometimes collectively known as big data - and the integration of such data with social scientific modes of enquiry a priority at the Faculty. We call this integration Social Data Science , with research carried out in an inter-departmental center comprising researchers from across the social sciences. Project Description The How Democracies Cope with Covid19: A Data-Driven Approach (HOPE) project constitutes an unprecedented research project which examines the interrelationship between the (a) trajectory of the COVID-19, (b) the decisions of governments and international organisations, (c) media and social media landscapes and (d) citizens’ behavior and well-being. To this end, we utilize the fact that the COVID-19 pandemic is unfolding in the middle of the “big data” revolution. For the first time in human history, we are able to measure with extreme precision and time-resolution how governments and citizens react (and with what consequences) during an extremely severe crisis. This PostDoc Project supports the overall HOPE project by analyzing large-scale data on the COVID-19 crisis, focusing on telecommunication, social media data, and human mobility data. The researcher will integrate with other branches of the HOPE project to understand the connection between these large-scale behavioral data and questionnaire data or anthropological field studies. Responsibilities and tasks The successful applicant will Analyze and model structures in large scale data, including mobility data collected from mobile phones, and social media data. Collaborate with researchers from both computational and social sciences in a truly interdisciplinary environment. Co-author scientific papers aimed at high-impact journals Participate in international conferences. Qualifications You should have a PhD degree or equivalent. You must have a background within physics, applied mathematics, machine learning, computational social science, or related fields. A track record of publishing interesting work within some of those fields. Experience analyzing large-scale datasets in Python. Experience with machine learning (incl) deep learning for prediction problems. Broader experience with programming is an advantage. Experience in time-series analysis is an advantage. Experience with modeling complex networks or human mobility is an advantage. Experience in Spark is an advantage. An active interest in strong collaborations and interdisciplinary work is a plus. An active interest in communicating science is a plus 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. The position is in the Section for Cognitive Systems at the Technical University of Denmark, which is a top Danish machine learning group. Both salary and working conditions are excellent. The group is a down-to-earth and fun place to be. SODAS is located in the heart of Copenhagen. Most group members live in Copenhagen which is often named as the best city in the world to live, and for good reasons. It's world renowned for food, beer, art, music, architecture, the Scandinavian "hygge", and much more. In Denmark, parental leave is generous, and child-care is excellent and cheap. Salary and terms of employment 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 period of employment is 2 years starting 1 January 2021. You can read more about career paths at DTU here . Further information Further information may be obtained from Professor Sune Lehmann, email@example.com . You can read more about DTU Compute at www.compute.dtu.dk/english . Application procedure Please submit your online application no later than 6 December 2020 (local time) . We are interested in a speedy process, thus applications submitted earlier will be considered as they arrive. 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: Application (cover letter) CV Diploma (MSc/PhD) List of publications Applications and enclosures received after the deadline will not be considered. A ll interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply. 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 12,000 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 and in Sisimiut in Greenland.
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