PhD Spatial-Temporal Data Analysis

PhD Spatial-Temporal Data Analysis

Published Deadline Location
6 Nov 20 Dec Eindhoven

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Job description

Are you passionate about developing novel spatial-temporal statistical models and see the impact of your research? And are you eager to work with professionals from other scientific disciplines to implement your research? Do you aim to grow into an independent researcher that works at the edge between methodological innovation and application? Then you could be the next PhD student at our statistical data science impact group TRI-DSA [Teaching & Research Institute for Data Science Analytics] at the department of Mathematics and Computer Science (M&CS) of the Eindhoven University of Technology (TU/e).

Job Description

The department of Mathematics and Computer Science (M&CS) of the Eindhoven University of Technology (TU/e) started recently a statistical data science research and impact group under the name of Teaching and Research Institute for Data Science Analytics (TRI-DSA: https://tri-dsa.win.tue.nl/) The goal of TRI-DSA is to deliver trustworthy and state-of-the-art data science analytics to society through contract research, research support, professional courses & workshops, and development of (user-friendly) software and codes. Researchers working at TRI-DSA collaborate with professionals and researchers from internal and external organizations and companies on challenging data science problems. The current focus of TRI-DSA is on data science analytics for health and life sciences and in the data science research area of spatial and temporal data among others. TRI-DSA has several interesting ongoing collaborations (with e.g., pharma, hospitals, registries, eMTIC, ICMS, data science start-ups) and is in need of PhD student to support the research activities of TRI-DSA.

The PhD candidate should be interested in
  • Developing and improving statistical data science techniques for real health and life science applications in the area of spatial-temporal data.
  • Collaborating with non-data science professionals.
  • Acting as research consultant for specific requests of the partners of TRI-DSA.
  • Supporting the professional education and life-long learning activities of TRI-DSA.

The research focuses on developing generic spatial-temporal Poisson models (STPM's) that can adequately describe time-dynamic event rates across geographic areas and incorporate individual or aggregated geographic information. The main directions within the research will be developing spatial-temporal covariance structures, numerical (Bayesian and/or Frequentist) estimation methods, approaches for incomplete and missing information, and causal frameworks. An important element of the research will be the validation of the novel or improved data science analytics and the creation of easy-to-use algorithms and software. The intended PhD thesis will thus consists of both theoretical and applied work. The PhD candidate will be supervised and working with the researchers and collaborators of TRI-DSA.

An important aspect of the research is that it is being implemented (or at least ready for implementation) at external organizations and companies that are or will be working with TRI-DSA. TRI-DSA is currently working with medical spatial-temporal data from inhabitants of rural counties of the South of the USA, covid-19 data from different clinics in the Netherlands, and traveling disease survey data across the world.

Specifications

Eindhoven University of Technology (TU/e)

Requirements

We are looking for a PhD candidate who either has or is willing to get the knowledge and skills to be working with innovative spatial-temporal data science analytics in a dynamical and multi-disciplinary environment. Additionally, we are looking for a PhD candidate who has
  • A master's degree in data science, computer science, or mathematics (or equivalently).
  • Experience in conducting innovative data science projects.
  • Affinity with applied statistical data science.
  • Strong programming and software skills for data science analytics (Python, R, SAS).
  • A team work attitude.
  • The ability to work in a dynamic and multi-disciplinary environment.
  • Strong presenting and reporting skills.
  • Fluency in spoken and written English.

Conditions of employment

A meaningful job in a dynamic, ambitious, and inclusive university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:
  • Full-time employment for five years, with an intermediate evaluation (go/no-go) after twelve months. You will spend 30% of your employment on impact and consultancy tasks at partners of TRI-DSA.
  • Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities. A PhD salary will start at € 2,770,=  in the first year and will grow to € 3,539,= in the fourth year.
  • A year-end bonus of 8.3% and annual vacation pay of 8%.
  • High-quality training programs and other support to grow into a self-aware, autonomous scientific impact researcher. At TU/e we challenge you to take charge of your own learning process.
  • An excellent technical infrastructure, on-campus children's day care and sports facilities.
  • An allowance for commuting, working from home and internet costs.
  • A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

Specifications

  • PhD
  • Engineering
  • max. 38 hours per week
  • University graduate
  • V32.7061

Employer

Eindhoven University of Technology (TU/e)

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Location

De Rondom 70, 5612 AP, Eindhoven

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