Vitaldata Analytics with AI to Improve Healthcare Decision-Making

Context

In our Medical Information Technology (MIT) department, we are involved in various research projects related to health. As a student assistant, intern, or student writing your thesis, you would have the opportunity to work with biosignal data and use your technical skills to develop innovative solutions with conventional- and spiking neural networks.

In our research project, we use real-world sensor data collected anonymously from various vital sensors (ECG, respiratory impedance, acceleration, etc.) to improve decision-making in sleep research with artificial intelligence. As part of the project, you would have the opportunity to work in your own area of interest - including image processing and machine vision.

If you want to use your technical skills to positively impact healthcare, apply for this exciting position!

Tasks

• You will start with your own research to be up-to-date on the latest technologies in the field of neural networks and vital signs analysis.
• You will analyse real-world data from ambulatory exams to improve healthcare decision-making.
• You will design and implement algorithms for the analysis of biosignal data with conventional and spiking neural networks.
• You will work with our research team on projects in the field of data analysis and biosignal data.

Requirements

• You are studying electrical engineering or information technology (bachelor's or master's)
• You are interested in the topic and (possibly) have initial experience with artificial intelligence and/or biosignal data.
• You have good programming skills and experience with Python programming language and its tools.
• You are motivated and have good communication skills.
• You have good written and spoken German and/or English skills.