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PhD project on Machine Learning for Dynamic Complex Network Analysis at Technical University of Denmark

DTU Compute would like to invite applications for a 3-year PhD position with earliest possible starting date September 1, 2020 (starting time negotiable). The position is financed by the DFF project “Learning the Structure and Dynamics of Complex Networks” and the PhD will be supervised by Professor Morten Mørup and Professor Sune Lehmann at the Section for Cognitive Systems, DTU Compute.

The project will develop novel computational frameworks for the analysis of dynamic social networks. In particular, the project will significantly advance upon the modeling of dynamic networks by enhancing considerably the ability to analyze massive networks through dynamic embeddings. The tools developed will allow us to visualize dynamic network structure, and forecast future interactions between entities. The project will exploit stochastic large-scale optimization frameworks and parallel computations using PyTorch/TensorFlow and derive efficient statistical machine learning modeling tools for large dynamic network analyses. The tools developed will be general and extended from linear to non-linear dynamic modeling using deep learning sequence modeling approaches. The project will further develop a predictive engine in which the learned models can be used efficiently to forecast future time-steps.

The developed dynamic network analysis tools will be used to analyze imminent challenges within our digital society enabling us to describe the dynamics of knowledge production, predict information propagation, and spot filter bubbles. The project comprises an interdisciplinary team of researchers with the necessary competences within machine learning and social network analysis. The project includes a research stay 3-6 month at project collaborator Professor Martin Rosvall (MR) at UmeĂĽ University who is an expert in statistical modeling of networks using information theoretic compression and key developer of important network modeling tools including InfoMap (mapequation.org)

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 time-series analysis and 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 one of the general degree programmes at DTU. For information about our enrolment requirements 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 Morten Mørup and Professor Sune Lehmann (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. Most group members live in Copenhagen which is often named as the best city in the world to live, and for good reasons. Its world renowned for food, beer, art, music, architecture, the Scandinavian "hygge", and much more.  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 full-time and the period of employment is 3 years beginning 1 September 2020 or according to mutual agreement.

You can read more about career paths at DTU here.

Further information
Further information may be obtained from Professor Morten Mørup, tel.: +45 2729 2975, email: mmor@dtu.dk.

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

Application
Please submit your online application no later than 1 August 2020 (23:59 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 (incl. list of publications or other research experience)

  • Grade transcripts and BSc and MSc diplomas

  • Excel sheet with translation of grades to the Danish grading system and course names translated into English (see guidelines and Excel spreadsheet here)

  • An example technical text you have written in English such as a report prepared for a course, a consulting project, or a published peer-reviewed scientific article.


 
If one or more of the items requested above is missing, the application will be considered invalid.

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.

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