DTU compute would like to invite applications for a 3-year PhD position starting May 1th. The project is financed by the Villum Foundation.
Project Description
Every cell phone call, credit card transaction, online comment, and email check is recorded in a database somewhere. Each day, millions of people share digital photographs, watch television online, and record and share their GPS tracks. Governments and city councils are recording and sharing comprehensive statistics on public spending, crime statistics, and public health. Almost every aspect of our daily lives is being captured in great detail—and we expect the rate of information growth to accelerate. Rich digital traces of this kind are something altogether novel and hold the potential to fundamentally change how we quantify and understand human behavior and human nature.
Over the past decade networks have become a key approach to understanding systems of interacting objects, unifying the study of diverse phenomena including biological organisms and human society. An increasing number of scientists have seized upon ‘slices’ of data considering, e.g. the patterns of cell phone communication, email communication, or online friendships alone. While such studies reveal interesting properties of human interrelations, it is clear that the full complexity of human interactions is expressed on many communication channels: face-to-face conversation, phone, text message, email, online chat, and online social networks, such as Facebook or Twitter. Due to the limited bandwidth of human attention, we usually only communicate on one channel at time, but shift effortlessly between the different modes of communication.
The overarching goal of this proposal is to take advantage of the recent technological developments in order to push the current boundaries of a quantitatively based understanding of social systems. Specifically, our aim is to record the network of social interactions with very high resolution (both in terms of temporal sampling and number of recorded communication channels) and develop mathematical approaches to describe and understand this highly complex and dynamic network. We record data using smartphones as sensors (or sociometers).
The successful candidate will focus particularly on topics related to the role of information stored in ties between individuals, as well as privacy in networked systems. The PhD contains elements of practical development work for the project, as well as theoretical work.
Requirements
Candidates must have a master degree in computational science and engineering, physics, applied mathematics, or engineering, or equivalent academic qualifications. Preference will be given to candidates who can document strong programming ability, and in addition have a background in statistics and mathematical modeling. Furthermore, a firm command of the English language is essential.
Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in the ITMAN Graduate School Programme of DTU Compute. Information about the general requirements for enrolment and the general planning of the scholarship studies is included in the general rules at DTU, which may be obtained here.
Salary and appointment terms
The salary and appointment terms are consistent with the current Danish rules for PhD degree students.
Further Information
Further information concerning the project can be obtained from Associate Professor, Sune Lehmann.
Further information concerning the application is available at the DTU Compute PhD homepage, the DTU Compute Graduate School ITMAN homepage or by contacting the responsible ITMAN Graduate School coordinator: Ulla Jensen, phone: + 45 4525 3359.
Application
Applications must be submitted in English as one single PDF, and we must have your online application by April 1th, 2013. Please open the link in the red bar "apply online" (“ansøg online”).
Applications must include:
Project Description
Every cell phone call, credit card transaction, online comment, and email check is recorded in a database somewhere. Each day, millions of people share digital photographs, watch television online, and record and share their GPS tracks. Governments and city councils are recording and sharing comprehensive statistics on public spending, crime statistics, and public health. Almost every aspect of our daily lives is being captured in great detail—and we expect the rate of information growth to accelerate. Rich digital traces of this kind are something altogether novel and hold the potential to fundamentally change how we quantify and understand human behavior and human nature.
Over the past decade networks have become a key approach to understanding systems of interacting objects, unifying the study of diverse phenomena including biological organisms and human society. An increasing number of scientists have seized upon ‘slices’ of data considering, e.g. the patterns of cell phone communication, email communication, or online friendships alone. While such studies reveal interesting properties of human interrelations, it is clear that the full complexity of human interactions is expressed on many communication channels: face-to-face conversation, phone, text message, email, online chat, and online social networks, such as Facebook or Twitter. Due to the limited bandwidth of human attention, we usually only communicate on one channel at time, but shift effortlessly between the different modes of communication.
The overarching goal of this proposal is to take advantage of the recent technological developments in order to push the current boundaries of a quantitatively based understanding of social systems. Specifically, our aim is to record the network of social interactions with very high resolution (both in terms of temporal sampling and number of recorded communication channels) and develop mathematical approaches to describe and understand this highly complex and dynamic network. We record data using smartphones as sensors (or sociometers).
The successful candidate will focus particularly on topics related to the role of information stored in ties between individuals, as well as privacy in networked systems. The PhD contains elements of practical development work for the project, as well as theoretical work.
Requirements
Candidates must have a master degree in computational science and engineering, physics, applied mathematics, or engineering, or equivalent academic qualifications. Preference will be given to candidates who can document strong programming ability, and in addition have a background in statistics and mathematical modeling. Furthermore, a firm command of the English language is essential.
Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in the ITMAN Graduate School Programme of DTU Compute. Information about the general requirements for enrolment and the general planning of the scholarship studies is included in the general rules at DTU, which may be obtained here.
Salary and appointment terms
The salary and appointment terms are consistent with the current Danish rules for PhD degree students.
Further Information
Further information concerning the project can be obtained from Associate Professor, Sune Lehmann.
Further information concerning the application is available at the DTU Compute PhD homepage, the DTU Compute Graduate School ITMAN homepage or by contacting the responsible ITMAN Graduate School coordinator: Ulla Jensen, phone: + 45 4525 3359.
Application
Applications must be submitted in English as one single PDF, and we must have your online application by April 1th, 2013. Please open the link in the red bar "apply online" (“ansøg online”).
Applications must include:
- application (letter of motivation)
- CV
- documentation of a relevant completed M.Sc. or M.Eng.-degree
- course and grade list of bachelor and master degrees
- Calculation of the weighted grade average, see guidelines here
All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.
Application Deadline : 1 April 2013
