Vacancies

Postdoc (CWI, Amsterdam): Learning utility functions for Negotiation & Intelligent Control

Autonomous control requires a model of the preferences for the user (or users) to be represented. This model must deal with partial information and uncertainty, which may be addressed with techniques from function approximation and machine learning/planning under uncertainty. The Grid-Friends project has a vacancy for a postdoctoral researcher to address local control in smart energy cooperatives, in charge of optimizing the activation of flexible assets and external negotiation commitments. The vacant position aims to build on meaningful representations of partial preference models, devise negotiation and/or control strategies given such models, and build novel preference elicitation algorithms to optimally query a user to improve utility function approximations (of an individual or a collective).

Postdoctoral researchers on evolutionary algorithms, machine learning, and biomechanical modelling to innovate automated registration of medical images

CWI closely collaborates with the Academic Medical Center (AMC) in Amsterdam to work on innovations in the medical domain along the entire spectrum from algorithmic foundations to clinical integration. Currently, CWI and AMC have a joint project for which we seek multiple talented postdocs to work on novel combinations of multi-objective evolutionary algorithms, machine learning, and biomechanical modelling for deformable image registration

PhD students on evolutionary algorithms, machine learning, and biomechanical modelling to innovate automated registration of medical images

CWI closely collaborates with the Academic Medical Center (AMC) in Amsterdam to work on innovations in the medical domain along the entire spectrum from algorithmic foundations to clinical integration. Currently, CWI and AMC have a joint project for which we seek multiple talented PhD students to work on novel combinations of multi-objective evolutionary algorithms, machine learning, and biomechanical modelling for deformable image registration.

PhD Student on the subject of CT imaging for Technical Art History: Algorithms and Techniques

Many objects in cultural heritage collections have a rich 3D internal structure. While the visible outer surface has been crafted with a focus on aesthetics, many of the secrets about the process of crafting the object are hidden beneath the surface, invisible to the naked eye. X-Ray CT is a powerful tool for creating detailed 3D images of the interior of such objects. However, its application to the study of cultural heritage collections is not straightforward, as the objects cover many length scales and have widely varying compositions.

PhD Student in the research project 'Mixed-Integer Non-Linear Optimisation: Algorithms and Applications' (MINOA)

The research project is part of the Marie Skłodowska-Curie Action Innovative Training Network MINOA funded under the Horizon 2020 programme. The MINOA ITN is an interdisciplinary research and training network consisting of 11 academic partners and six industrial partners in France, Germany, Italy and the Netherlands. The job is a full-time PhD position (Early Stage Researcher) in the field of Mathematical Optimization. A special focus is on the development and analysis of algorithms for polynomial optimization problems. These are non-linear optimization problems, involving polynomial constraints and variables which can be binary, continuous, or non-commutative. Such problems arise in many areas in operations research, discrete optimization and quantum information. The objective is to design new methods and algorithms using combinatorial and algebraic techniques combined with linear and semidefinite optimization.

PhD Student on the subject of Ultra-Fast 3D Reconstruction

Centrum Wiskunde & Informatica (CWI) and the Mathematical Institute of Leiden University seek a dedicated candidate for a PhD position in the interdisciplinary field of Mathematical Analysis, Algorithms and Computation for Tomography. As a PhD student, you will be part-time embedded in the Computational Imaging group at CWI, and part-time in the Analysis and Dynamical Systems group of the Mathematical Institute of Leiden University. As a team, we develop cutting-edge techniques for advanced tomographic reconstruction, combining expertise from Mathematics (Inverse Problems and Dynamical Systems), Computer Science (Efficient Algorithms and High Performance Computing), and Physics (Image Formation Modelling). Our goal is to develop novel computational methods for 3D and 4D imaging.

Postdoc / Postdoctoral Researcher on the subject of the computer-science aspects of quantum computing and quantum information theory

This position involves research into the computer-science aspects of quantum computing and quantum information theory. Specifically, the project will focus on one or more of the following topics: quantum algorithms and complexity, quantum machine learning, quantum communication, quantum cryptography. Depending on the most suitable topic, the research will be in collaboration with one or more of the following researchers: Jop Briët, Harry Buhrman, Peter Grünwald, Stacey Jeffery, Maris Ozols, Christian Schaffner, Michael Walter, and Ronald de Wolf. The position is on the NWO-funded QuantERA project QuantAlgo, for one or two years, and can start at any time after 1 August 2018.

Internship at CWI Amsterdam (duration 6 months) for business development of a novel product idea in energy flexibility trading

Energy systems are currently in a revolutionary transition, due to the increasing inclusion of sustainable energy sources. Whereas in the past, energy supply was determined by demand and was supplied centrally, in the future, demand and increasingly decentralized supply will need to respond to each other. Their balancing requires a combination of adjusting conventional generation, exploiting efficient storage technologies and implementing demand response with corresponding incentives thereof. Balancing activities may take place on multiple scales, from the individual household to the European or even an envisioned global grid. The transition to smart energy systems is changing business processes, markets and exchange traded products for balancing flexibility.

Internship at CWI Amsterdam (duration 6 months) for optimisation/machine learning on a novel product idea in energy flexibility trading

Energy systems are currently in a revolutionary transition, due to the increasing inclusion of sustainable energy sources. Whereas in the past, energy supply was determined by demand and was supplied centrally, in the future, demand and increasingly decentralized supply will need to respond to each other. Their balancing requires a combination of adjusting conventional generation, exploiting efficient storage technologies and implementing demand response with corresponding incentives thereof. Balancing activities may take place on multiple scales, from the individual household to the European or even an envisioned global grid. The transition to smart energy systems is changing business processes, markets and exchange traded products for balancing flexibility.

Postdoc on the subject of hybrid polystore query language design and implementation

TYPHON is an EU H2020 project, which aims at providing an industry-validated methodology and integrated technical offering for designing, developing, querying, evolving, analysing and monitoring scalable hybrid data persistence architectures that will meet the growing scalability and heterogeneity requirements of the European industry. Designing and deploying a hybrid data persistence architecture that involves a combination of relational and NoSQL databases, and which can manage different types of structured and textual data (polystores for conciseness), is a complex, technically challenging, and error-prone task.

PhD Student in the joint industrial PhD program with Xinhuanet on the subject of Social Internet of Things

We live in a society based on experiences. Whether we look at a commercial for a holiday destination or interact with social media, the consumer experience plays a crucial role in our behavior. Yet, it is surprising to see how little it is actually known about how consumers value these experiences. The high-end technical solutions for shaping experiences sharply contrast with the rather conventional mechanisms used to measure them. DIS explores the use of smart textiles and wearable sensors as a source for collecting reliable and quantified data about everyday life experiences. In particular, we are interested on better understanding social IoT in the environment of smart cities. Based on realistic testing grounds, collaborating with several commercial and academic partners, we have deployed our technology and infrastructure in places such as the National Theatre of China in Shanghai and the Amsterdam Dance Event in the Netherlands. Our approach is to seamless connecting fashion and textiles with sensing technology, and with the environment. The final objective is to create intelligent and empathic systems that can react to the experience of users.

PhD Student on the subject of Verification of Mainstream Java Libraries

The overall objective of this PhD position is the development and application of formal methods to actual software. Of particular interest are the mainstream libraries of the popular programming language Java. These libraries are widely used and therefore their correctness is of the utmost importance. This research builds on and extends the successful verification by means of the interactive theorem prover KeY of executable Java versions of Counting sort and Radix sort. A recent attempt to verify the Java implementation of the TimSort hybrid sorting algorithm as provided by the Java Collections Framework (and which is designed to perform well on real world data) revealed a fundamental error which for certain inputs crashed the software. In close collaboration with the Software Engineering group of TU Darmstadt, we succeeded in the verification of the corrected software. Motivated by this success our overall goal is the systematic verification of the Java Collections Framework.

Postdoc on the subject of Machine Learning and Space Weather

The position involves research in machine learning techniques and Bayesian inference, applied to real-time forecasting of energetic electrons in the Earth radiation belts. These electrons can be harmful to satellites, whose disruption can potentially lead to catastrophic societal and economic events. The emerging field of Space Weather is concerned with making accurate predictions of such dangerous events, sufficiently in advance so that countermeasures can be taken. The aim of this project is to advance our space weather prediction capability by enhancing physics based models with a new data-driven probabilistic framework. The project will involve state-of-the-art numerical simulations, Bayesian parameters estimation, uncertainty quantification and machine learning techniques.

Document Actions