![greenTEG AG](https://media.trabajo.org/img/noimg.jpg)
Experienced Data Scientist: Algorithm Development
Vor 5 Tagen
greenTEG, a spin-off of ETH Zurich, is developing innovative sensor solutions targeting the wearables market. For the development of algorithms to detect and track physiological parameters, we are looking for a data scientist with expertise in
modeling physiological time-series data.
Tasks
As part of the R&D team, you will
- prepare and analyze recorded sensor data in Python
- improve our current core body temperature algorithm and implement new ideas for tracking physiological parameters
- document your progress in detail, write reports and case studies
- coordinate technical progress with external university and medical partners
- take over responsibilities for the project
**Requirements**:
You have a valid Master’s (or equivalent) university degree in mathematics, statistics, computer science, physics or engineering and at least 2 years of experience in algorithm development based on physiological time series data.
Furthermore, you have to be experienced in
- Python language for numerics, data analysis and machine learning
- data mining, processing and analysis
- statistics, machine learning concepts, pipelines and algorithms
- working with physiological time series data
- understanding the physics of heat flow and thermal conduction
- project management
A valid work permit for Switzerland or an EU citizenship is mandatory.
Please provide sample Python code from one of your reference projects in
**Benefits**:
Welcome to our team
We offer a collegial and striving work environment in a motivated,
dynamic and high-tech oriented team.
Interested? - Join us
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Zurich, Schweiz greenteg AG VollzeitgreenTEG, a spin-off of ETH Zurich, is developing innovative sensor solutions targeting the wearables market. analysis or early detection of diseases. For the development of algorithms to detect and track physiological parameters, we are looking for a data scientist with expertise in modeling physiological time-series data. **Preferred start date**:...
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