We are looking for a Research Intern (6 months preferred minimum 4 months) to join our team in Berlin. You will contribute to our cutting-edge research at the intersection of machine learning healthcare and signal processing. The internship provides hands-on experience in developing and evaluating ML models for healthcare applications with a focus on audio data. We also offer the opportunity to co-author scientific papers develop skills in scientific publishing and present findings in scientific congresses.
This position is open both for internships and Masters thesis projects. If you are considering a thesis we are happy to discuss suitable research directions together.
Tasks
As a Research Intern you will:
- Pursue ongoing research on voice-based prediction of heart failure decompensation.
- Design run and analyze ML experiments using real large-scale datasets from our prestigious clinical partners such as Charité Mayo Clinic and UCSF.
- Contribute to building a reproducible and interpretable ML research environment.
- Assist in preparing results for clinical studies and potential publications.
- Present your research findings to both technical and non-technical collaborators.
Requirements
We are looking for candidates who have:
- Fluency in English (working language).
- Strong background in machine learning and data science (Python).
- Familiarity with ML frameworks and libraries (e.g. PyTorch XGBoost scikit-learn etc).
- Curiosity and motivation to explore challenging research in an interdisciplinary field at the interface of AI and medicine.
- Interest in working on an impactful subject that can directly affect peoples lives.
- Soft skills: ability to work with some autonomy and to present research results clearly to different audiences.
Benefits
- On-site internship in our Berlin office.
- Compensation: comfortable stipend to cover living in Berlin without counting.
We are looking for a Research Intern (6 months preferred minimum 4 months) to join our team in Berlin. You will contribute to our cutting-edge research at the intersection of machine learning healthcare and signal processing. The internship provides hands-on experience in developing and evaluating M...
We are looking for a Research Intern (6 months preferred minimum 4 months) to join our team in Berlin. You will contribute to our cutting-edge research at the intersection of machine learning healthcare and signal processing. The internship provides hands-on experience in developing and evaluating ML models for healthcare applications with a focus on audio data. We also offer the opportunity to co-author scientific papers develop skills in scientific publishing and present findings in scientific congresses.
This position is open both for internships and Masters thesis projects. If you are considering a thesis we are happy to discuss suitable research directions together.
Tasks
As a Research Intern you will:
- Pursue ongoing research on voice-based prediction of heart failure decompensation.
- Design run and analyze ML experiments using real large-scale datasets from our prestigious clinical partners such as Charité Mayo Clinic and UCSF.
- Contribute to building a reproducible and interpretable ML research environment.
- Assist in preparing results for clinical studies and potential publications.
- Present your research findings to both technical and non-technical collaborators.
Requirements
We are looking for candidates who have:
- Fluency in English (working language).
- Strong background in machine learning and data science (Python).
- Familiarity with ML frameworks and libraries (e.g. PyTorch XGBoost scikit-learn etc).
- Curiosity and motivation to explore challenging research in an interdisciplinary field at the interface of AI and medicine.
- Interest in working on an impactful subject that can directly affect peoples lives.
- Soft skills: ability to work with some autonomy and to present research results clearly to different audiences.
Benefits
- On-site internship in our Berlin office.
- Compensation: comfortable stipend to cover living in Berlin without counting.
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