Working Student (m/f/d) Machine Learning / Data Science at Fresenius Group

Join our mission to enhance the lives of patients with chronic kidney failure using data-driven solutions, advanced algorithms, and artificial intelligence. At Fresenius Medical Care, our global innovation unit taps into a unique data reservoir, combining the development, operation, and application of dialysis machines with access to extensive technical and medical data. We are dedicated to developing cutting-edge solutions for patients, doctors, and clinics, aiming to make advanced therapies accessible worldwide.

Your Challenge in Detail

As a member of our team, you will:

• Support the development of analytics solutions for both in-center and home dialysis topics.
• Engage in the entire development process, from data acquisition to algorithm deployment and monitoring.
• Enhance existing machine learning models.
• Perform data analyses and derive insights using proper statistical methods.

Your Competence is in Demand

We are looking for candidates with:

• Current advanced full-time studies in computer science, statistics, or a related field.
• Proficiency in English (both written and spoken).
• Solid foundation in statistics, including distributions, hypothesis tests, and correlation.
• Basic understanding of machine learning algorithms and concepts.
• Experience with data analysis and visualization using Python.
• Familiarity with data science libraries and frameworks such as NumPy, Pandas, and Scikit-Learn.
• Knowledge of deep learning and libraries like Keras and PyTorch is advantageous.
• Initial experience with self-supervised learning, Large Language Models (LLMs), Git, unit testing, and command line interface operations is a plus.

Job Details

Start: ASAP
Duration: 12 months, with an option to extend
Working hours: Approximately 20 hours per week
Location: Berlin (Mobile working possible by arrangement; regular on-site presence required)

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Company name: Fresenius Group
Job title: Working Student (m/f/d) Machine Learning / Data Science