PhD position in Biostatistics and Machine Learning
PhD position in Biostatistics and Machine Learning
Published | Deadline | Location |
---|---|---|
today | 7 May | Rotterdam |
Job description
The experience of stress is an inherent aspect of daily life. However, can we validly measure this, and how and under what circumstances does it contribute to disease? We at the Department of Biostatistics at the Erasmus University Medical Center Rotterdam are looking for a Ph.D. student to work with us on the ambitious Stress in Action project (more details about the project can be found here ).
The NWO gravitation project Stress in Action capitalizes on fast technological advances and big data analytics to move stress research from the lab to daily life. You will be part of the data analytic support core (DASC) team. The DASC will develop a variety of big data analytics approaches. Specific analytical questions for DASC include: (1) How can we derive counterfactual predictions of stress outcomes with multiple time-varying stress exposures? (2) How can we assess the accuracy of counterfactual predictions?
More specifically, you will work on novel combinations of joint models for longitudinal and time-to-event data with machine learning techniques. The primary aim is to derive causal predictions to enable (clinical) decision-making. This position primarily focuses on research, but the Ph.D. student is also expected to assist in the teaching and consulting responsibilities of the department.
The supervisors for this project are Professor Dimitris Rizopoulos and Professor Ellen Hamaker.
Specifications
- max. 36 hours per week
- €2789—€3536 per month
- Rotterdam View on Google Maps
Erasmus MC (University Medical Center Rotterdam)
Requirements
- MSc degree (or finishing soon) in Statistics, Mathematics, Computer Science, or a related discipline.
- Knowledge of mixed-effects or multilevel models, survival analysis, and machine-learning techniques.
- Familiarity with Bayesian statistics Programming skills in R; familiarity with Python is also a plus.
- Affinity and preferably experience with writing research papers.
- Good social and communication skills and willingness to work with other team members.
- Enthusiastic about translating scientific insights into practical guidelines and advice.
Conditions of employment
- You will receive a temporary position for 4 years starting September 1, 2023.
- The gross monthly salary is € 2.789 ,- in the 1st year and increases to € 3.536,- in the 4th year (scale OIO). This is based on 36 hours per week.
- 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 2/3 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.
Employer
Erasmus MC
The Department of Biostatistics of Erasmus MC is well known for its innovative statistical research in analyzing complex data structures (longitudinal and survival data, correlated data, missing data, censored data, misclassification data, Bayesian techniques, and smoothing techniques).
Additional information
For more information about this position, please contact Prof. dr. Dimitris Rizopoulos:
d.rizopoulos@erasmusmc.nl/ secretariat.biostatistics@erasmusmc.nl.
If you are interested in applying for this position, please provide the following documents:
- Letter of motivation.
- CV (including contact information for at least two academic references).
- Transcripts from your bachelor's and master's degree.
- An R script file showcasing your programming capabilities.
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Application procedure
For more information about this position, please contact Prof. dr. Dimitris Rizopoulos:
d.rizopoulos@erasmusmc.nl/ secretariat.biostatistics@erasmusmc.nl.
If you are interested in applying for this position, please provide the following documents:
- Letter of motivation.
- CV (including contact information for at least two academic references).
- Transcripts from your bachelor's and master's degree.
- An R script file showcasing your programming capabilities.
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