2 PhD positions in Statistics
2 PhD positions in Statistics
You cannot apply for this job anymore (deadline was 15 Mar 2018).
Browse the current job offers or choose an item in the top navigation above.
Job description
Stochastics (STO):
The section comprises chairs in probability, statistics, and stochastic operation research. It is one of the three sections with Mathematics of the Department of Mathematics and Computer Science.
The research program in probability studies random spatial structures and its applications in statistical physics and networking, with a focus on random networks, spin systems and self-interacting random processes. The main aim is to identify the scaling behavior for these systems, by applying methodology such as large deviations, combinatorial expansions and coupling techniques.
The research program in statistics develops, studies and compares statistical methods for collecting and analyzing complex structured and multivariate data sets. These methods include parameter estimation, Bayesian analysis, model fitting, latent variable models, mixed models, missing data, process control, survival & reliability theory, time series analysis, statistical learning methods, and causality. Among the central themes is the analysis of high-dimensional temporal data sets and other large data sets, but analysis of small data sets are not neglected. The research is driven and inspired by applications from engineering and health and life sciences. The group actively explores new research lines in Data Science and maintains many strong ties with industry, including biopharmaceutical companies, chemical industry, high-tech companies and medical centers.
The research program in stochastic operations research focuses on systems that operate in the presence of randomness. It aims at developing mathematical models and methods for the design, analysis, optimization and control of such systems. A large part of the research effort is devoted to queueing theory and the analysis of random walks related to it. Some of the queueing research is of a fundamental nature, and much of it is inspired by problems in production and logistics and in computer-communication systems.
Positions in Statistics:
The statistics group collaborates intensively with national and international scientific research groups from different data science disciplines (mathematical statistics, industrial statistics, biostatistics, chemometrics, epidemiologists, etc.) The statistics group is interested in both theoretical and applied work. Additionally, the group has a strong industrial network with large Dutch industries and institutes to be able to fuel and implement their research. Through the existing collaborations, the statistics group has access to a few relevant (high-frequent) multivariate longitudinal data sets that provides some interesting analysis challenges that are in need of a solution. The group is also trying to modernize their teaching concepts by using new teaching approaches.
The statistics group has openings for two PhD students (for a period of four years). The candidates will work on a STW-project called 'Rapid micro statistics' that is a collaboration with three international pharmaceutical companies and it is funded by the Dutch national science foundation NWO (www.stw.nl/nl/content/rapid-micro-statistics). The PhD students will work on challenging statistical methods for data analysis of microbiological test methods (one on qualitative and one on quantitative methods). The candidate will work closely with a post-doc and the two project leaders.
The section comprises chairs in probability, statistics, and stochastic operation research. It is one of the three sections with Mathematics of the Department of Mathematics and Computer Science.
The research program in probability studies random spatial structures and its applications in statistical physics and networking, with a focus on random networks, spin systems and self-interacting random processes. The main aim is to identify the scaling behavior for these systems, by applying methodology such as large deviations, combinatorial expansions and coupling techniques.
The research program in statistics develops, studies and compares statistical methods for collecting and analyzing complex structured and multivariate data sets. These methods include parameter estimation, Bayesian analysis, model fitting, latent variable models, mixed models, missing data, process control, survival & reliability theory, time series analysis, statistical learning methods, and causality. Among the central themes is the analysis of high-dimensional temporal data sets and other large data sets, but analysis of small data sets are not neglected. The research is driven and inspired by applications from engineering and health and life sciences. The group actively explores new research lines in Data Science and maintains many strong ties with industry, including biopharmaceutical companies, chemical industry, high-tech companies and medical centers.
The research program in stochastic operations research focuses on systems that operate in the presence of randomness. It aims at developing mathematical models and methods for the design, analysis, optimization and control of such systems. A large part of the research effort is devoted to queueing theory and the analysis of random walks related to it. Some of the queueing research is of a fundamental nature, and much of it is inspired by problems in production and logistics and in computer-communication systems.
Positions in Statistics:
The statistics group collaborates intensively with national and international scientific research groups from different data science disciplines (mathematical statistics, industrial statistics, biostatistics, chemometrics, epidemiologists, etc.) The statistics group is interested in both theoretical and applied work. Additionally, the group has a strong industrial network with large Dutch industries and institutes to be able to fuel and implement their research. Through the existing collaborations, the statistics group has access to a few relevant (high-frequent) multivariate longitudinal data sets that provides some interesting analysis challenges that are in need of a solution. The group is also trying to modernize their teaching concepts by using new teaching approaches.
The statistics group has openings for two PhD students (for a period of four years). The candidates will work on a STW-project called 'Rapid micro statistics' that is a collaboration with three international pharmaceutical companies and it is funded by the Dutch national science foundation NWO (www.stw.nl/nl/content/rapid-micro-statistics). The PhD students will work on challenging statistical methods for data analysis of microbiological test methods (one on qualitative and one on quantitative methods). The candidate will work closely with a post-doc and the two project leaders.
Specifications
- max. 38 hours per week
- Eindhoven View on Google Maps
:fill(white)/logos/tue-en-wide_acOLN2b.png)
Eindhoven University of Technology (TU/e)
Requirements
The PhD candidates have an MSc degree in mathematics preferably with a specialization in statistics or stochastics or an equivalent type of master degree (e.g. econometrics). The candidates have a strong affinity with real applications, good communication skills, English speaking and writing skills, and a willingness to learn Dutch.
Conditions of employment
We offer:A challenging job for 4 years in a dynamic and ambitious university and a stimulating research environment; Support with your professional and personal development; A gross salary per month of € 2222,- (first year) as a PhD up to € 2840,- (final year) in accordance with the Collective Labor Agreement of the Dutch Universities 8% holiday allowance 8.3% end of the year allowance. An extensive package of fringe benefits (e.g. support in moving expenses, excellent technical infrastructure, on-campus child care, and excellent sports facilities.
