1 Postdoctoral researcher and 2 PhD candidates in Causal Inference at Faculty of Science – Informatics Institute. Applications are invited 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. The successful candidates will be based in theAmsterdam 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.
- Salary indication: €2,125 to €3,908 gross per month
- Deadline: 1 October 2015
- Vacancy number: 15-310
The Faculty of Science holds a leading position internationally in its fields of research and participates in a large number of cooperative programs with universities, research institutes and businesses. The faculty has a student body of around 4,000 and 1,500 members of staff, spread over eight research institutes and a number of faculty-wide support services. A considerable part of the research is made possible by external funding from Dutch and international organizations and the private sector. Since September 2010, the whole faculty has been housed in a brand new building at the Science Park in Amsterdam. The instalment of the faculty has made the Science Park one of the largest centres of academic research in The Netherlands.
The Informatics Institute is one of the large research institutes with 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 active in a dynamic scientific area, with a strong innovative character and an extensive portfolio of externally funded projects.
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’).
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.
We are looking for highly motivated and creative individuals who enjoy working in a multidisciplinary research environment.
Applicants for the PhD candidate positions need:
- a Master’s degree in computer science, artificial intelligence, mathematics, statistics, physics or closely related area;
- a solid understanding and working knowledge of modern probabilistic machine learning and statistics;
- hands-on experience with causal discovery methods or probabilistic graphical modelling will be a plus.
- a PhD degree (or equivalent qualification) in computer science, statistics, applied mathematics, bioinformatics, physics, or a related field of study;
- an exceptional scientific track record, documented by publications at first-tier journals and conferences;
- a strong research background in causal inference, probabilistic machine learning or statistics.
In addition, all successful applicants should have:
- excellent mathematical skills (especially in probability theory and statistics, calculus, and linear algebra);
- excellent programming skills (preferably in at least one of the following languages: C++, Python, MatLab, R);
- strong communication, presentation and writing skills and excellent command of English;
- a strong interest in developing algorithms for applications on large-scale data analysis problems in biology;
- commitment and a cooperative attitude.
Informal inquiries can be made by email to:
Preferred starting date: November 2015 (later starting date is possible).
The appointment for the PhD candidates will be on a temporary basis for a period of 4 years (initial appointment will be for a period of 18 months and after satisfactory evaluation it can be extended for a total duration of 4 years) and should lead to a dissertation (PhD thesis). An educational plan will be drafted that includes attendance of courses and (international) meetings. The PhD student is also expected to assist in teaching of undergraduates.
Based on a full-time appointment (38 hours per week) the gross monthly salary will range from €2,125 in the first year to €2,717 in the last year. There are also secondary benefits, such as 8% holiday allowance per year and the end of year allowance of 8.3%. The Collective Labour Agreement (CAO) for Dutch Universities is applicable.
The appointment for the postdoctoral researcher will be full-time (38 hours a week) on a temporary basis for a period of three years. The initial appointment will be for a period of 12 months and after satisfactory evaluation it will be extended with two more years. The postdoctoral researcher is expected to assist in teaching of undergraduates and in supervising PhD students. The gross monthly salary will be in accordance with the University regulations for academic personnel, and will range from €2,476 up to a maximum of €3,908 (scale 10) based on a full-time appointment depending on qualifications, expertise and on the number of years of professional experience. The Collective Labour Agreement for Dutch Universities is applicable. There are also secondary benefits, such as 8% holiday allowance per year and the end of year allowance of 8.3%.
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.
Applications may be submitted by sending your application to firstname.lastname@example.org. To process your application immediately, please quote vacancy number 15-310 and the position you are applying for in the subject-line.
Applications for the PhD candidate positions must include:
curriculum vitae, a motivation letter that explains why you have chosen to apply for this specific position, a copy of your Master’s thesis, a complete record of Bachelor and Master courses (including grades), and the names and contact information of two academic references (please do not include any recommendation letters). All these should be grouped in a single PDF attachment.
Applications for the postdoctoral researcher position must include:
curriculum vitae, a motivation letter that explains why you have chosen to apply for this specific position, a list of publications, a statement of your research experience and interests and how these relate to this project, a complete record of Bachelor and Master courses (including grades), a copy of your PhD thesis, (URLs pointing to) your top two publications, and the names and contact information of three academic references (please do not include any recommendation letters). All these should be grouped in a single PDF attachment.
Applications will be accepted until 1 October 2015. The committee does not guarantee that late or incomplete applications will be considered.