Merck, Internship - ADC modeling

Azienda
Merck
Sede
Corsier-sur-Vevey, Svizzera
Durata
6 mesi. Inizio 1 gennaio 2027 
Indennità
Retribuito + benefit
Area professionale
Chimica/Farmaceutica Statistica/Data Analysis

Attività

  • Support the development and evaluation of the UV-Vis-based soft sensor, including data preprocessing and chemometric data treatment.
  • Develop kinetic reaction models using gPROMS and/or Python to describe the evolution of the conjugation species.Compare different kinetic model structures, estimate kinetic parameters, and assess the predictive performance.
  • Validate the kinetic model against independent experimental or offline analytical data where available.Combine kinetic model with the soft sensor data using an Extended Kalman Filter.
  • Evaluate the ability of the hybrid model to update the estimated reaction state and predict the reaction progress.Identify data gaps and, if required, design and perform additional small-scale conjugation experiments.
  • Analyze model performance, robustness and limitations.
  • Plan and execute experiments in collaboration with PAT, modelling and process experts.Ensure that experimental conditions and results are accurately recorded and traceable.
  • Develop Python-based tools for data preparation, visualization, and analysis.Present your results during project reviews and prepare a final technical report.

Requisiti principali

  • Currently in master’s or Engineering student in data science, analytical chemistry, biochemistry, biotechnology, chemical engineering or a related field.
  • Strong interest in reaction kinetics, mechanistic modelling, dynamic systems, and data science.
  • Experience with python and gPROMS or another process modelling tool is a strong plus.
  • Interest in spectroscopy and chemometrics; knowledge of UV-Vis or PLS is an advantage.
  • Practical laboratory experience and strong attention to data quality and reproducibility.
  • Knowledge of Kalman filtering is a plus.
  • Curious, rigorous, proactive, and able to work independently as well as in a
  • multidisciplinary team.
  • Fluent in English
Coesione Italia GDL 2021-2027
Cofinanziato dall'Unione Europea
Ministero del Lavoro e delle Politiche Sociali

Il progetto Stage4eu è cofinanziato dal Programma Nazionale Giovani, Donne e Lavoro FSE+ 2021 – 2027 (Piano INAPP 2023-2029)