Pharma Process Modeling & Data Science Intern

Johnson Johnson; Schaffhausen; On-site; CHF 17,000 - 21,000; Part time

Job summary

Johnson & Johnson in Schaffhausen, Switzerland is seeking a Master’s student or recent graduate for a 6‑month internship in the Process Science Modeling and Data team. You will join a multidisciplinary group working on data-driven manufacturing processes, solvent recovery, and process optimization, gaining hands-on industry experience.

Ideal candidates have a Master’s degree in a related field or are close to completing one, with Python-based data analytics experience and strong communication

Qualifications

• Enrolled in or recently graduated from a Master's program in Chemical Engineering, Biological Engineering, Chemistry, Physics, Mechanical Engineering, Pharmaceutical Sciences, Engineering field or related.
• Experience with python-based data analytics.
• Experience with modeling and programming (e.g., Python, MATLAB, R, gPROMS, Aspen Plus, or other relevant software).
• Motivated, entrepreneurial approach.
• Good problem‑solving skills.
• Excellent verbal and written communication skills.

Responsibilities

• Join a multidisciplinary team at the intersection of data science, process modeling, and pharmaceutical manufacturing.
• Data science tasks: Clean, preprocess, and analyze manufacturing process data from existing datasets.
• Modeling and process simulation tasks: Support projects on distillation and solvent recovery process modeling; perform simulation and optimization studies.

Skills

Problem Solving

Process Modeling

Education

Master's degree in Chemical Engineering, Biological Engineering, Chemistry, Physics, Mechanical Engineering, Pharmaceutical Sciences or related field

Tools

Python

MATLAB

R

gPROMS

Aspen Plus

Job description

Johnson & Johnson in Schaffhausen, Switzerland is seeking a Master’s student or recent graduate for a 6‑month internship in the Process Science Modeling and Data team. You will join a multidisciplinary group working on data-driven manufacturing processes, solvent recovery, and process optimization, gaining hands-on industry experience.

Ideal candidates have a Master’s degree in a related field or are close to completing one, with Python-based data analytics experience and strong communication