Assistant Professor in Biostatistics

1 maand geleden

Rotterdam, Zuid-Holland, Nederland Erasmus MC Voltijd

Job Description

The Department of Biostatistics and Epidemiology at Erasmus MC is seeking a highly motivated Assistant Professor to establish a new research line in the intersection of statistics, causal inference, and machine learning. This position will focus on research, teaching, and consulting activities, and will be part of a dynamic team that produces innovative statistical and machine-learning methods to answer clinical, epidemiological, and public health research questions.

Key Responsibilities

  • Conduct research in biostatistics and epidemiology, with a focus on developing new statistical methods and applying them to real-world problems.
  • Teach and mentor students in biostatistics and epidemiology, and contribute to the development of new courses and programs.
  • Collaborate with clinical researchers and other stakeholders to design and conduct studies, and to translate research findings into practice.
  • Develop and maintain a strong research program, with a focus on securing external funding and publishing research in top-tier journals.
  • Contribute to the department's teaching and consulting activities, and participate in departmental and university service.

Requirements

  • PhD degree in Statistics, Computer Science, or a related field.
  • Strong research and teaching background in biostatistics and epidemiology.
  • Excellent communication and collaboration skills, with the ability to work effectively with diverse stakeholders.
  • Ability to secure external funding and publish research in top-tier journals.
  • Experience with statistical software and programming languages, such as R or Python.

What We Offer

  • A competitive salary and benefits package, including a 13th month and individual travel expense package.
  • A dynamic and supportive work environment, with opportunities for professional growth and development.
  • Access to state-of-the-art research facilities and resources, including a strong computing infrastructure and a collaborative research environment.
  • The opportunity to work with a diverse team of researchers and clinicians, and to contribute to the development of innovative statistical and machine-learning methods.

How to Apply

Interested candidates should submit a letter of motivation, CV, and a piece of methodological work for which they feel most proud. Please do not contact the department directly.

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