PhD student in Health Data Science

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Job Description - PhD student in Health Data Science

Job description

The department of Medical Informatics is looking for a PhD student to work on cutting-edge health AI and data science topics. This research will be performed in close collaboration with the Observational Health Data Sciences and Informatics (OHDSI) initiative, which is a global, multi-stakeholder, interdisciplinary collaborative to bring out the value of health data through large-scale analytics () which develop frameworks to generate reliable real-world evidence.

As a PhD student, you will be responsible for the research on using federated data networks to improve best practices around the development and validation of prediction models. You will lead and contribute to projects conducting methodological research within the field of machine learning in healthcare. Research will be performed in clinical settings, feature engineering methods, deep-learning, and other advanced machine-learning methods to support personalized medicine. The research will focus on using large-scale federated data networks made possible by the standardization of health data to the OMOP Common Data Model. Impact assessments of these new approaches on patient care are part of the research agenda.

Work environment

A healthy population and excellence in healthcare through research and education. This is what Erasmus MC stands for. Conducting groundbreaking work, pushing boundaries, and leading the way in research, education, and healthcare. We are practical people with a high level of expertise, working hard to improve and renew the healthcare of today and the public health of tomorrow.

Our institute is internationally at the forefront of health data science and offers a dynamic, challenging, and cooperative research environment. The department of Medical Informatics is specialized in using routine healthcare data. Currently the department is coordinating and collaborating in several projects that aim at building EU-wide and global federated data networks. The advisors for the PhD students will include dr. Ross Williams, dr. Jenna Reps and dr. Peter Rijnbeek.

Qualifications and skills

  • We encourage applications from candidates with a background in Natural Sciences, Informatics, Economics, Sociology and Data Science.
  • Interest in data mining, deep-learning, machine learning, regression analysis and programming is required.
  • We invite candidates who are working in the regulatory domain or are interested in applying health data science in their clinical setting, to propose research topics. These candidates preferably have a medical background.
  • The candidates must be highly motivated, willing to learn and demonstrate initiative in assigned tasks.
  • Good written and verbal communication skills are desired for this international project.
  • Before you apply please check our .

    Terms of employment

  • You will receive a temporary position for 4 years.The gross monthly salary is € 3.017 ,- in the 1st year and increases to € 3.824,- in the 4th year (scale OIO).
  • Excellent fringe benefits, such as a 13th month that is already paid out in November and a individual travel expense package.
  • Pension insurance with ABP. We take care of approximately 70% of the monthly contribution.
  • Special benefits, such as a incompany physiotherapist and bicycle repairer. And there is also a gym where you can work on your fitness after work.
  • More information

    For more information about this position, please contact Ross D. Williams, project lead, via or e-mail . See also .

    If you are excited by the thought of this position and would like to apply, please do so by using the application form on our website.

    No agencies please.

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