Internship - ADC modeling (m/f/d)

The role is an internship focused on ADC modeling, part of a company that innovates in Healthcare, Life Science, and Electronics. The company aims to enrich lives through science and technology, with a strong focus on developing medicines, intelligent devices, and innovative technologies in areas like Oncology, Neurology, and Fertility. The internship is based in Corsier-sur-Vevey and will last for six months, starting on 1st January 2027. The main day-to-day responsibilities include supporting the development and evaluation of a UV-Vis-based soft sensor, developing kinetic reaction models using gPROMS and/or Python, and validating these models against experimental data. The intern will also combine kinetic models with soft sensor data using an Extended Kalman Filter, evaluate the hybrid model's performance, and plan and execute experiments in collaboration with experts. Additionally, the intern will develop Python-based tools for data preparation, visualization, and analysis, and present results during project reviews. Must-have requirements include being a master's or Engineering student in data science, analytical chemistry, biochemistry, biotechnology, chemical engineering, or a related field. Fluency in English is also required. The intern should have a strong interest in reaction kinetics, mechanistic modeling, dynamic systems, and data science. Practical laboratory experience and a strong attention to data quality and reproducibility are essential. Nice-to-have skills include experience with Python and gPROMS or another process modeling tool. Knowledge of spectroscopy and chemometrics, particularly UV-Vis or PLS, is an advantage. Familiarity with Kalman filtering is also beneficial. The intern should be curious, rigorous, proactive, and able to work independently as well as in a multidisciplinary team. The location, Corsier-sur-Vevey, offers a diverse, inclusive, and flexible working culture with opportunities for personal development and career advancement. What the role asks for: - Currently in master's or Engineering student in data science, analytical chemistry, biochemistry, biotechnology, chemical engineering or a related field. - Fluency in English - Strong interest in reaction kinetics, mechanistic modelling, dynamic systems, and data science. - Practical laboratory experience and strong attention to data quality and reproducibility. - Nice-to-have: Experience with Python and gPROMS or another process modelling tool. - Nice-to-have: Knowledge of spectroscopy and chemometrics, particularly UV-Vis or PLS. - Nice-to-have: Familiarity with Kalman filtering.