Data Science Internship: Gas Sensing & Time‑Series Analytics

VAT Vakuumventile AG; Lavamünd; Hybrid; EUR 18.000 - 25.000; Teilzeit

Zusammenfassung

VAT Group is offering an internship in experimental data science for gas sensing and time-series analytics in Haag, St. Gallen, CH. You will combine hands-on experimentation with data science to study gas dynamics in a vacuum chamber using advanced sensors.

The role covers experimental planning, data collection, preprocessing, feature engineering, time-series modelling and model validation. You will learn to work with vacuum technology, sensor systems and multichannel data.

Qualifikationen

• Pursuing MSc in data science, ML, physics, math or related field.
• Basic knowledge of data analysis, statistics, signal processing, or ML.
• Programming experience in Python or MATLAB.
• Good written and spoken English.

Aufgaben

• Familiarize with vacuum technology, gas dynamics, process chambers and sensor systems.
• Support the setup and execution of experiments in the vacuum test lab.
• Plan experiments using a structured Design of Experiments approach.
• Collect and organize multivariate time-series data from sensors.
• Develop data-preprocessing workflows for synchronization, filtering and quality.
• Explore relationships between sensor signals, gas properties and process conditions.
• Develop and compare data-driven methods for classification, prediction, monitoring, anomaly detection.
• Validate methods with independent experiments and varying conditions.
• Document procedures, datasets, modelling results and limitations.
• Present findings to engineers and researchers.

Kenntnisse

Python

MATLAB

Statistics

Data analysis

Machine learning

Ausbildung

MSc in data science or related field

Tools

scikit-learn

PyTorch

TensorFlow

MATLAB

Jobbeschreibung

VAT Group is offering an internship in experimental data science for gas sensing and time-series analytics in Haag, St. Gallen, CH. You will combine hands-on experimentation with data science to study gas dynamics in a vacuum chamber using advanced sensors.

The role covers experimental planning, data collection, preprocessing, feature engineering, time-series modelling and model validation. You will learn to work with vacuum technology, sensor systems and multichannel data.