Computational social science

[Update: the book is now available, go get it!]

Rejoice! There is a new book on temporal networks coming out soon — Temporal Network Theory, edited by Petter Holme & myself. A lot has happened in temporal-network research since our first edited volume (Temporal Networks, 2013); in this new volume, we wanted to focus on the theoretical side of things & invited contributions from many pioneering scientists & groups.

As a teaser trailer, here is a list of the book’s chapters:

A Map of Approaches to Temporal Networks—Petter Holme and Jari Saramäki
Fundamental Structures in Temporal Communication Networks—Sune Lehmann
Weighted, Bipartite, or Directed Stream Graphs for the Modeling of Temporal Networks—Matthieu Latapy, Clémence Magnien, Tiphaine Viard
Modelling Temporal Networks with Markov Chains, Community Structures and Change Points—Tiago P. Peixoto and Martin Rosvall
Visualisation of Structure and Processes on Temporal Networks—Claudio D. G. Linhares, Jean R. Ponciano, Jose Gustavo S. Paiva, Bruno A. N. Travençolo, Luis E. C. Rocha
Weighted Temporal Event Graphs—Jari Saramäki, Mikko Kivelä, Márton Karsai
Exploring Concurrency and Reachability in the Presence of High Temporal Resolution—Eun Lee, James Moody, Peter J. Mucha
Metrics for Temporal Text Networks—Davide Vega and Matteo Magnani
Bursty Time Series Analysis for Temporal Networks—Hang-Hyun Jo and Takayuki Hiraoka
Challenges in Community Discovery on Temporal Networks—Remy Cazabet and Giulio Rossetti
Information Diffusion Backbone—Huijuan Wang and Xiu-Xiu Zhan
Continuous-Time Random Walks and Temporal Networks—Renaud Lambiotte
Spreading of Infection on Temporal Networks: An Edge-Centered Perspective—Andreas Koher, James P. Gleeson, and Philipp Hövel
The Effect of Concurrency on Epidemic Threshold in Time-Varying Networks—Tomokatsu Onaga, James P. Gleeson, and Naoki Masuda
Dynamics and Control of Stochastically Switching Networks: Beyond Fast Switching—Russell Jeter, Maurizio Porfiri, and Igor Belykh
The Effects of Local and Global Link Creation Mechanisms on Contagion Processes Unfolding on Time-Varying Networks—Kaiyuan Sun, Enrico Ubaldi, Jie Zhang, Márton Karsai and Nicola Perra
Supracentrality Analysis of Temporal Networks with Directed Interlayer Coupling—Dane Taylor, Mason A. Porter, and Peter J. Mucha
Approximation Methods for Influence Maximization in Temporal Networks—Tsuyoshi Murata and Hokuto Koga

Update: I’ve now hired a postdoc, so this call is no longer open.

I just got the news that I have the funds for hiring a postdoc, so here we go! Interested? Read on! Know someone? Share the link!

So:

I am looking for a postdoc (1+1) years, starting as soon as possible
Topic: somewhere in the intersection of (temporal) networks + computational social science + data science. Depends on your interests and experience!
Place: Department of Computer Science, Aalto University, Espoo, Finland

Application procedure:

Let’s do this light folks! If you are interested or would like to know more, please send me an email (firstname.lastname@aalto.fi) where you briefly describe what you have done so far and what your research interests are. Let me know of any research ideas that fit the above topic! No CV’s or publication lists or PDF attachments at this stage, please! I’ll ask for them later.

I’ll wait at least a couple of weeks to get applications and then we’ll do Skype interviews. Apologies if I cannot answer your email immediately; I’m on parental leave (see below).

What you’ll get:

A great working environment, access to high-quality data, nice colleagues, an international research group with a healthy gender balance, a city/country where things just work, almost endless summer sunlight in compensation for dark winters, decent salary and other benefits (good healthcare), and did I say a great working environment? (We don’t do 80-hour workweeks; no-one expects anyone to work in the weekends; even full professors like me can go on long parental leave; and still we get things done—this is Scandinavia!)

If any present/former colleagues are reading this, feel free to add comments below!

What makes a good candidate:

You should have decent knowledge of complex networks, computational social science, and/or methods of data science, with some published papers; programming skills are required (we mostly use Python and C++ whenever more speed is needed); you should sort of know what you want to do (=have your own research interests). Teaching and supervision experience is a bonus. And of course, you should be a nice human being 🙂

Want to know more? Send me an email or add a comment below!

Cheers,

Jari