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Laatste vacatures

PhD student, within the research project OPTIMAL

A key component of machine learning is mathematical optimization, that is used, for example, to train neural networks. The goal of this project is to provide new analysis and tools for optimization problems and algorithms arising in machine learning, but also to use insights and tools from machine learning to improve optimization methods. This explains the project title 'Optimization for and with machine learning'. The project consists of four connected work packages.

The first two work packages are related to 'optimization for machine learning'.
In the first work package we will investigate why the optimization methods currently used in machine learning are often successful in practice and analyse the limits of their computational tractability.
The second work package is aimed at enhancing the existing optimization algorithms and developing new ones to obtain more accurate machine learning models in an efficient way.

The last two work packages are related to 'optimization with machine learning'.
The third work package is aimed at using machine learning to obtain data-centric approximation and optimization algorithms. We will develop algorithms that adapt to the specific data characteristics of the problem instance. The advantage of such data-centric algorithms is more accurate solutions and/or less computation time.
In the fourth work package we will develop a data-centric optimization modelling approach. In such an approach parts of the resulting optimization model are obtained via machine learning. This data-centric modelling can be used to get more accurate models or can be used in cases where there is no theoretical knowledge available to build the model manually. In addition, we will test our insights on a variety of applications where the consortium members are already involved, including classification problems in the medical sciences, decision problems related to the UN World Food Programme, and routing of shared, self-driving cars.

The PhD student will work on topics related to work package 3.
The main objectives will be to design and analyse of algorithms for basic machine learning tasks, broadly construed. The emphasis will be on developing new theoretical concepts and rigorous methods, based on techniques from optimization and going beyond worst-case analysis, to understand the behaviour of learning-augmented algorithms on real-world data. In addition, the goal will be to use the developed techniques to design new algorithms that exploit (machine-learning) predictions and provide (provable) performance guarantees.

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14-07-2021 Centrum Wiskunde & Informatica
PhD student for Responsible Recommenders in the Public Library

This research project, funded by the KB National Library of the Netherlands, explores the practical implementation of ethical AI principles in the context of book recommendations for public library users. The goal is to design, develop and evaluate recommender systems not only in terms of end-user satisfaction, but also in terms of public values and ethical principles, such as inclusiveness, transparency and privacy. The project is a collaboration between CWI, KB, VU Amsterdam and Delft University of Technology. The PhD student will be co-hosted at CWI and the KB, and will become part of the Cultural AI ICAI Lab.

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30-06-2021 Centrum Wiskunde & Informatica
Postdoc on Transparent AI Pipelines for Information Quality Assessment

The postdoc will work in the context of the "The eye of the beholder: Transparent pipelines for assessing online information quality" project, funded by the Netherlands eScience Center, for three years.

The overall goal of the project is to investigate how to design AI pipelines that are fully transparent and tunable by an end-user. The pipeline will be applied to the task of automated information quality assessment, a task that can be perceived as subjective or biased, and that thus requires a high level of transparency and customisation to support specific scholarly requirements. The postdoc will be appointed by CWI and will collaborate with the Humanities faculty of the University of Amsterdam.

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14-06-2021 Centrum Wiskunde & Informatica
Post-doc position in the area of Spiking Neural Networks

The postdoc candidate will participate in the recently awarded NWO NWA ORC project "Acting under uncertainty". The goal of this project is to advance our understanding how humans are able to act in complex and uncertain circumstances, and how such knowledge can be applied to smooth our interaction with emerging autonomous vehicles. The whole project encompasses a broad spectrum of academic, industrial and societal partners and includes a large group of researchers. The postdoc position will advance state-of-the-art in spiking neural networks and their real-world applicability in applications like drones and other autonomous vehicles, and close collaboration is foreseen with labs at TU Delft, IMEC NL, and NLR. Some project management related tasks will also be part of the candidate's responsibilities.

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28-04-2021 Centrum Wiskunde & Informatica