1 Postdoc and 2 PhD positions in Causal Inference (University of Amsterdam)
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The University of Amsterdam invites applications for three fully funded
positions (two PhD candidates and one postdoctoral researcher) to work with dr.
Joris Mooij on the development and validation of new methods for causal
modelling, reasoning and discovery for systems involving feedback, with a
strong focus on applications in molecular biology. The position is part of the
ERC Starting Grant project 'CAFES: Causal Analysis of Feedback Systems', funded
by the European Research Council.
Application closing date: October 1, 2015
Preferred starting date: November 1, 2015 (later starting date is possible)
Duration: 4 years for the PhD positions;
3 years for the postdoc position.
About the project
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Causal inference, a branch of statistics and machine learning, studies how
cause-effect relationships can be discovered from data and how these can be
used to make predictions in situations where a system has been perturbed by an
external intervention. The ability to reliably make such predictions is of
great value for practical applications in a variety of disciplines. The
research will consist of the development of new theory and efficient algorithms
for robust discovery of causal relationships and estimation of causal effects
from a combination of observational data, interventional data, and background
knowledge. The focus will lie on the challenging but important class of systems
that involve causal feedback. A strong emphasis also lies on applications in
molecular biology, one of the most promising areas for automated causal
discovery from data, enabling a thorough validation of causal prediction
methods in practice. Successful applicants are expected to help develop this
research line, to assist in teaching and in supervising Master’s students. In
addition, the postdoctoral researcher is expected to assist in supervision of
the PhD students.
About the academic environment
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The successful candidates will be based in the Amsterdam Machine Learning Lab
(AMLab) led by prof. dr. Max Welling within the Informatics Institute of the
Faculty of Science of the University of Amsterdam, the Netherlands.
AMLab conducts research in the area of large scale modelling of complex data
sources. This includes the development of new methods for probabilistic
graphical models and nonparametric Bayesian models, the development of faster
(approximate) inference and learning methods, deep learning, causal inference,
reinforcement learning and multi-agent systems and the application of all of
the above to large scale data domains in science and industry ('Big Data
problems').
Some of the things we have to offer:
* competitive pay and excellent benefits;
* top-50 University worldwide;
* very friendly, interactive and international working environment;
* access to high-end computing facilities (cluster with 4,000+ cores);
* new building located near the city center (10 minutes by bicycle) of
one of Europe's most beautiful and lively cities.
English is the working language within the Informatics Institute. Since
Amsterdam is a very international city where almost everybody speaks and
understands English, candidates need not be afraid of the language barrier.
Further information
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For further information, including instructions on submitting an application,
see the official job ads at:
http://www.uva.nl/en/about-the-uva/working-at-the-uva/vacancies/item/15-310_1-postdoctoral-researcher-and-2-phd-candidates-in-causal-inference.html
Informal inquiries can be made by email to Joris Mooij (j.m.mo...@uva.nl).
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Joris Mooij | Assistant Professor
Amsterdam Machine Learning Lab (AMLab)
Informatics Institute | University of Amsterdam
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Science Park 904 | 1098 XH Amsterdam
+31 (0)20.525.8426
http://jorismooij.nl/
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