The “Machine Learning for Optimization of Patient Treatments” group at the Helmholtz Center Munich (HMGU) is inviting applications for multiple Postdoc or PhD positions to join the team to develop new data analytics for the optimization of patient pathways, using big data analysis methods on electronic medical records (EMR).
Qualifications:
- MSc or PhD degree in Computer Science, Statistics, Mathematics, Data Science or equivalent
- Strong background in machine learning (graphical models, Bayesian and neural networks), statistics, and preferably causal inference methods;
- Knowledge of and/or experience with time-series data, preferably clinical data;
- Programming expertise in Python, R, and SQL;
- Interest and/or experience in working with healthcare problems (particularly surgical procedures);
- Demonstrated skill in scientific writing;
- Excellent interpersonal skills with the ability to work independently and in collaboration with a multidisciplinary team of surgeons and engineers.
- Experience with healthcare data and building real-world systems is a plus.
Duration: initially limited to three years
Applications:
- Applications to be sent to Dr. Narges Ahmidi (narges.ahmidi@helmholtz-muenchen.de) including:
- Cover letter
- CV
- Contact information for two references
—————–Quick Overview————- | |
Organization | Technical University of Munich (TUM) |
Country | Germany |
Fellowship Level | Postdoctoral/Doctoral |
Subject areas | Computer Science, Statistics, Mathematics, Data Science |
Fellowship amount | Varies |
Eligibility | PhD/Master’s degree |
Deadline | Varies |
———————————— |