PhD Project in Representations of Social Behavior

onsdag 24 jun 20

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Frist 1. august 2020
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DTU Compute’s Sections for Cognitive Systems, would like to invite applications for a 3-year PhD position starting September 1st, 2020. The project is financed by the Villum Foundation Synergy Project “Nation-Scale Social Networks”, carried out jointly with the Center for Social Data Science (SODAS) at the University of Copenhagen. The PhD will be supervised by Professor Sune Lehmann and Professor Lars Kai Hansen at the Section for Cognitive Systems, DTU Compute.

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. 

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 researcher from across the social sciences. 

Project Description
The project will investigate representations of social behavior and how predictive such representations are for life outcomes (education levels, income and wealth ranks, unemployment histories) based on registry data at Statistics Denmark. The aim is to develop dense embeddings of life-event space, based on trajectories of life-events, using ideas from text embeddings (life2vec). Life-events and relations of very different contents can have similar ‘meaning’. In order to push the state-of-the-art, we will explore knowledge enhanced word-vectors and use temporal (not just sequence) information. Further, we will leverage the fact that there is a recent literature on predicting disease outcomes based on patient records. Based on sequences of ‘life-vectors’ representing the events of individual lives, we will use deep recurrent neural networks (LSTM/GRU) to predict our outcomes of interest. Further, explainability and interpretability are key considerations.

Responsibilities and tasks
The successful student will 

  • Analyze large scale registry data to create dense embeddings of life outcomes.
  • 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.
  • Participate advanced classes to improve your academic skillset
  • Carry out work in the area of dissemination and teaching as part of the overall PhD education.
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. You must have a master’s degree in engineering science or natural science or equivalent academic qualifications. You must have a very strong background within machine learning and programming in Python. Experience in complex network modeling is an advantage. You must be fluent in English, both speaking and writing and possess excellent communication skills. 

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 Professor Sune Lehmann, DTU Compute and Professor Lars Kai Hansen, DTU Compute. 

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 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 September 1st, 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 Professor Sune Lehmann at sljo@dtu.dk

Further information concerning the application is available at the DTU Compute
PhD homepage

Application
Please submit your online application no later than 1 August 2020 (local time). Applications must be submitted as a single 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 a single 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 and in Sisimiut in Greenland.