PhD Position in A.I. for Healthcare University of Zurich Department of Quantitative Biomedicine

Department of Quantitative Biomedicine Ph.D. Position in A.I. for healthcare 100 % The Krauthammer lab is looking for a motivated PhD candidate to work on projects in the intersection of healthcare, data science and machine learning with special emphasis on the analysis of patient's longitudinal data. Your responsibilities Our goal is to develop state-of-the-art approaches and build best-in-class methods to capitalize on digital clinical information to automatically compare, analyze and visualize complex longitudinal patient journeys focusing on the concept of patient journey similarity. This involves building robust decision support systems powered by (explainable and interpretable) predictive algorithms for guiding patient therapy across all disease stages, the assessment of treatment effects using counterfactual inference and the identification of causal mechanisms driving disease progression. Moreover, there are possibilities to expand the research scope towards working with heterogeneous biomedical data for patient stratification. Your profile Minimum qualifications: • Master's degree (MSc) in computer science (focused on machine learning), optimization, statistics, applied math or closely related discipline • Proficient in Python and the scientific computing stack (SciPy, Numpy, Scikit- learn, pandas) • Proficient in one of the deep learning frameworks (PyTorch, Tensorflow, or Jax) • Text editing using Markdown and LaTeX Additional (preferred) qualifications • Knowledge of statistical time series modelling and forecasting (such as autoregressive models and exponential smoothing) • Knowledge of ODE and SDE • Knowledge and experience in using/developing neural network (NN) models for time series / longitudinal data analysis • Knowledge of probabilistic graphical models (such as Gaussian processes, Neural Process, Bayesian inference or Bayesian NN) • Knowledge of explainable AI methods (i.e., model explainability and interpretability) • Experience using Linux systems • Experience using Docker and singularity containers • Experience using HPC infrastructure What we offer Access to state-of-the-art infrastructure (computational resources), clinical datasets and medical expertise domain-knowledge (excellent medical doctors and research scientists) Ability to make a real and tangible impact in healthcare research Solve real-world problems and improve hospital-related process and workflow Stimulating research environment and a place to grow academically and professionally Outstanding working conditions at the University of Zurich. Place of work Zurich, Switzerland Start of employment Employment start date to be mutally agreed. Further information Dr. Ahmed Allam Apply now If you apply for this position please say you saw it on Medicinoxy

Department of Quantitative Biomedicine

Ph.D. Position in A.I. for healthcare
100 %

The Krauthammer lab is looking for a motivated PhD candidate to work on projects in the intersection of healthcare, data science and machine learning with special emphasis on the analysis of patient's longitudinal data.

Your responsibilities

Our goal is to develop state-of-the-art approaches and build best-in-class methods to capitalize on digital clinical information to automatically compare, analyze and visualize complex longitudinal patient journeys focusing on the concept of patient journey similarity. This involves building robust decision support systems powered by (explainable and interpretable) predictive algorithms for guiding patient therapy across all disease stages, the assessment of treatment effects using counterfactual inference and the identification of causal mechanisms driving disease progression. Moreover, there are possibilities to expand the research scope towards working with heterogeneous biomedical data for patient stratification.

Your profile

Minimum qualifications:
• Master's degree (MSc) in computer science (focused on machine learning), optimization, statistics, applied math or closely related discipline
• Proficient in Python and the scientific computing stack (SciPy, Numpy, Scikit- learn, pandas)
• Proficient in one of the deep learning frameworks (PyTorch, Tensorflow, or Jax)
• Text editing using Markdown and LaTeX

Additional (preferred) qualifications
• Knowledge of statistical time series modelling and forecasting (such as autoregressive models and exponential smoothing)
• Knowledge of ODE and SDE
• Knowledge and experience in using/developing neural network (NN) models for time series / longitudinal data analysis
• Knowledge of probabilistic graphical models (such as Gaussian processes, Neural Process, Bayesian inference or Bayesian NN)
• Knowledge of explainable AI methods (i.e., model explainability and interpretability)
• Experience using Linux systems
• Experience using Docker and singularity containers
• Experience using HPC infrastructure

What we offer

Access to state-of-the-art infrastructure (computational resources), clinical datasets and medical expertise domain-knowledge (excellent medical doctors and research scientists)
Ability to make a real and tangible impact in healthcare research
Solve real-world problems and improve hospital-related process and workflow
Stimulating research environment and a place to grow academically and professionally
Outstanding working conditions at the University of Zurich.