Unlock the Power of Machine Learning in Healthcare
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This exciting opportunity is for a Scientific Assistant in Machine Learning for Healthcare to contribute to cutting-edge research and development.
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About the Role:
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* Analyze the latest machine learning literature on time series data processing and prediction tasks in intensive care units, utilizing datasets from national projects and public sources like MIMIC IV, HiRID, and eICU.
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* Develop deep learning models for predicting health outcomes, such as sepsis onset, mortality, and kidney failure, using multimodal time series data.
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* Enhance the models with personalization techniques to improve accuracy and effectiveness.
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* Publish research findings in reputable scientific publications.
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Your Profile:
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* Hold a Master's degree in Computer Science, Data Science, Machine Learning, Electrical and Computer Engineering, Computational Biology and Bioinformatics, Health Sciences and Technology, or related fields.
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* Demonstrate strong programming skills in Python and experience working with large datasets, high-performance computing environments, and Linux operating systems.
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* Have experience developing machine learning and deep learning models, preferably with TensorFlow and PyTorch.
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* Show excellent written and oral communication skills in English and a willingness to learn about biomedical applications of machine learning and deep learning models.
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* Demonstrate ability to work independently and collaboratively in a team environment.
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Preferred Qualifications:
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* Experience with project development in deep learning models.
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* Knowledge of model fairness, robustness, and domain adaptation.
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* Familiarity with multimodal time series data.
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* Publications in machine learning or sensor data processing-oriented conferences, workshops, or symposia.
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* Swiss/EU citizenship or Swiss work permit holder preferred due to tight timeline.
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