Virtual Physiological Human Conference 26 - 28 September 2016

Virtual Physiological Human Conference 26 – 28…

6 days ago Brecht Schipper
VPH2016 offers an exciting program of state-of-the art science & engineering in computational (bio)medicine, ranging from foundational research on multiscale modelling of human (patho) physiology, via underpinning research on data science and infrastructures for the virtual physiological human,…
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6 days agoVirtual Physiological Human Conference 26 – 28…
Postdoctoral researcher multiscale cell based blood flow modelling and simulation, 38 hours per week

Postdoctoral researcher multiscale cell based bloo…

2 weeks ago Brecht Schipper
The Informatics Institute of the Faculty of Science is one of the large research institutes in the faculty, with a focus on complex information systems divided in two broad themes: 'Computational Systems' and 'Intelligent Systems'. The institute has a prominent international standing and is acti…
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2 weeks agoPostdoctoral researcher multiscale cell based bloo…
PhD candidate in Machine Learning for Risk Management in Trading Activities

PhD candidate in Machine Learning f…

4 weeks ago Brecht Schipper
PhD candidate in Machine Learning for Risk Management in Trading Activities Quantitative Analytics, ING Bank Amsterdam NL Institute for Informatics, University of Amsterdam The Quantitative Analytics group at ING Bank Amsterdam together with the Institute for Informatics at University of Amsterdam invites an application for an Early Stage Researcher (ESR) PhD scholarship in the…
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4 weeks agoPhD candidate in Machine Learning f…
CSL wins a EU H2020 Marie Sklodowska-Curie Innovative Training Network call in the BigData Finance project

CSL wins a EU H2020 Marie Sklodowsk…

4 weeks ago Brecht Schipper
The project Machine Learning Algorithms for Risk Management in Trading Activities will be supervised by Dr. Drona Kandhai and Prof. Peter Sloot. The main objective is to develop a prototype framework for pricing and risk management using machine learning  algorithms and a large variety of heterogeneous and high-volume data, including tick-by-tick quotes of bond prices, market data underl…
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4 weeks agoCSL wins a EU H2020 Marie Sklodowsk…
Vacancy: Assistant professor ‘Information Processing in Complex Adaptive Systems', 30,4 to 38 hours per week

Vacancy: Assistant professor ‘Information Processi…

2 months ago Brecht Schipper
This Assistant professor (A/P) position will be within the Computational Science Laboratory (CSL), Informatics Institute, Faculty of Science at the University of Amsterdam. This research driven laboratory concentrates on novel ways to model and simulate the highly complex world around us. CSL co…
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2 months agoVacancy: Assistant professor ‘Information Processi…

“Nature is a Complex System that processes information. Computational Science aims to make the complexity of those systems tractable.”


Group Mission

We live in a highly connected and strongly coupled world, and are surrounded by a large diversity of complex systems. All these systems have one thing in common: they process information. We aim to understand this information processing in such dynamic multi-level complex systems.

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Can we detect and describe the computational structure in dynamic processes and can we provide a quantitative characterization of essential aspects of this structure? When modeling for instance traffic in a city, the interactions between the individuals driving the cars, the bicycles, and pedestrians result in a dynamic self-organizing interaction structure, which is superimposed on the road network. This can be seen as a dynamical computational structure where information is exchanged, stored, and processed. What are the essential aspects of this structure, and how do they determine the way in which information is actually stored, transferred, and processed in complex systems? And what does that mean for the overall system behavior, that is, for their emergent properties? Can we then better understand emergent properties and critical phenomena such as tipping points? For instance, where do traffic jams come from, which all of sudden seem to appear from thin air? Or, can we get a deeper understanding of the systemic economic crises that struck us in 2008? Are we able to steer or control such emergent properties? What can we do to prevent traffic jams while maintaining the throughput on the road? Maybe by bringing down velocity, or slightly controlling the traffic entering a road on the individual car level? Or more dramatically, can we ‘nudge’ the behavior of countries, large companies, and/or individuals to fight the climate change? The ever increasing and abundant availability of data, both from science and society, drives our research. We study complex systems in the context of methods like multi-scale cellular automata, dynamic networks and individual agent based models. The challenges include data-driven modeling of multi-level systems and their dynamics as well as conceptual, theoretical and methodological foundations that are necessary to understand these processes and the associated predictability limits of such large-scale computer simulations.