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Postdoc in Modeling and Visualizing Events in Connected Human Lives - DTU Compute

Danmarks Tekniske Universitet (DTU)



Postdoc in Modeling and Visualizing Events in Connected Human lives will be creating representational learning models of registry data.
DTU Compute’s Sections for Cognitive Systems, would like to invite applications for a 2-year postdoc position starting 1 January 2025. The postdoc 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.

Project Description
The project is part of a larger project (Nation Scale Social Networks) which investigates 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. We are currently working on developing dense embeddings of life-event space, based on trajectories of life-events, using ideas from text embeddings (see https://www.researchsquare.com/article/rs-2975478/v1). That work leverages a recent literature on predicting disease outcomes based on patient records and explainability and interpretability are important considerations in our modeling.

This project will work on extending those ideas by identifying strategies for how to use network data to connect the individuals in the data. The networks are based on data already contained in Statistics Denmark (family relations, joint workplaces, etc). In this sense, the work will focus on understanding the role of social networks for life outcomes.

The idea is to address the role of the network in stages. Firstly, we will explore how well can we predict life outcomes by incorporating network data in the individual-level representations. Secondly, we will explore how to compare individual-level event sequences and network features in a unified framework.

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 research 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 researcher from across the social sciences.

Responsibilities and qualifications
The successful applicant will:

  • Analyze and model structures in large scale data.
  • Collaborate with researchers from both computational and social sciences in an interdisciplinary environment.
  • Co-author scientific papers aimed at high-impact journals
  • Participate in international conferences.

Qualification

  • You must hold a PhD degree (or equivalent).
  • You must have a background within physics, applied mathematics, computer science or related fields.
  • A track record of publishing interesting work within some of those field.
  • Experience with machine learning, incl deep learning
  • Experience with modeling complex networks or graph neural networks is an advantage.
  • Experiences using transformers is an advantage.
  • Experience working with Natural Language Processing is an advantage.
  • Experience analyzing event-sequences is an advantage.
  • Experience with data visualization is an advantage.
  • Experience in time-series analysis 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.

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. Desired start date of employment is 1 January 2025.

You can read more about career paths at DTU here.

Further information
Further information may be obtained from Professor Sune Lehmann, [email protected].

You can read more about DTU Compute at www.compute.dtu.dk.

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark.

Application procedure
Your complete online application must be submitted no later than 26 November 2024 (23:59 Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", 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
  • Academic Diplomas (MSc/PhD – in English)
  • List of publications
  • Any recommendations you wish to include

Applications received after the deadline will not be considered.

All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates for the position.

DTU Compute
DTU Compute is a unique and internationally recognized academic department with 385 employees and 11 research sections spanning the science disciplines mathematics, statistics, computer science, and engineering. We conduct research, teaching and innovation of high international standard – producing new knowledge and technology-based solutions to societal challenges. We have a long-term involvement in applied and interdisciplinary research, big data and data science, artificial intelligence (AI), internet of things (IoT), smart and secure societies, smart manufacturing, and life science. At DTU Compute we believe in a diverse workplace with a flexible work-life balance.

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 mission to develop and create value using science and engineering to benefit society. That mission lives on today. DTU has 13,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.

Adresse:

Richard Petersens Pl.
2800 Kgs. Lyngby

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Danmarks Tekniske Universitet (DTU)

Anker Engelunds Vej 1, 2800 Kgs. Lyngby

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