Internship - Experimental Data Science for Gas Sensing and Time-Series Analytics

VAT Group, the world's leading supplier of high‑performance vacuum valves, is seeking an intern to support the creation of intelligent vacuum systems. The company, with more than 3,200 staff and manufacturing sites in Switzerland, Malaysia and Romania, develops components that are essential for semiconductor processing equipment worldwide. The internship blends hands‑on laboratory work with data‑science and machine‑learning activities focused on gas‑sensing and time‑series analytics. During the placement you will become acquainted with vacuum technology, gas dynamics and sensor hardware, then help set up and run experiments in the company's vacuum test lab. You will design experiments using a structured Design of Experiments methodology, gather multivariate time‑series data from several sensor types, and build preprocessing pipelines that synchronise, filter, segment and assess data quality. The role also involves exploring how sensor signals relate to gas properties and process conditions, developing and comparing data‑driven models, and validating those models with independent runs under varied operating scenarios. All work will be documented and presented to engineers and researchers, covering procedures, datasets, modelling approaches, results and any limitations. The ideal candidate is currently pursuing or has recently completed a master's degree in data science, machine learning, physics, mathematics, mechanical, electrical, chemical, control, mechatronics engineering or a closely related discipline. You should possess a solid foundation in data analysis, statistics, signal processing and basic machine‑learning concepts, as well as practical programming skills in Python, MATLAB or comparable tools. Experience or a strong interest in analysing multichannel time‑series data, performing feature engineering and validating models is required, together with a willingness to work directly with vacuum equipment, sensors and data‑acquisition hardware. Proficiency in written and spoken English, strong analytical thinking, the ability to learn independently and a collaborative attitude are also essential. Additional assets include familiarity with machine‑learning frameworks such as scikit‑learn, PyTorch or TensorFlow, and knowledge of Design of Experiments, laboratory measurement techniques or uncertainty estimation. An enthusiasm for vacuum technology, gas‑sensing, process control or semiconductor manufacturing would further strengthen your profile. The internship offers exposure to a global, interdisciplinary R&D team, the chance to contribute to cutting‑edge semiconductor equipment, and a supportive environment that encourages personal growth and the sharing of ideas. What the role asks for: - MSc student or recent graduate in relevant engineering or science field - Basic knowledge of data analysis, statistics, signal processing, ML - Programming experience in Python or MATLAB - Experience or interest in time‑series analysis and feature engineering - Willingness to work hands‑on with vacuum equipment and sensors - Good written and spoken English proficiency - Strong analytical thinking and independent learning ability - Collaborative mindset - Nice-to-have: experience with scikit‑learn, PyTorch, or TensorFlow - Nice-to-have: knowledge of Design of Experiments and uncertainty estimation