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Die Position
Pharmaceutical& Solid State Developmentis part of Pharma Technical Development and situated in Basel, Switzerland.
Our key expertise is the development of robust and economic processes for drug substances with tailor-made solid state properties and patient centric formulations for the synthetic molecule portfolio of projects from early clinical studies to commercialization. We advance the design and delivery of transformative medicines by combining particle engineering, characterization, and formulation development - ensuring optimal drug performance, manufacturability, and patient-centric solutions from molecule to medicine.
As an intern you will support the departmentPharmaceutical& Solid State Developmentin developing image-based machine learning workflows to characterize and classify spray-dried materials into distinct subpopulations.
The Opportunity
- Review of the relevant literature applicable to the project
- Training in relevant SOPs and manufacturing/analytical equipments
- Optimize and advance analytical characterization methods for spray-dried materials.
- Leverage machine learning to automate the classification and characterization of diverse particle shapes
- Regular discussion of project progress with supervisors and planning of next steps
- Summarize work in scientific reports and present results to the Roche Synthetic Molecule development community.
Who you are
You are a University student (or you graduated within 12 months prior to the start date) preferably in the subject of Pharmaceutical Sciences, Pharmaceutical Technology, Data Sciences, Cheminformatics or Chemistry and have an interest in technical and analytical issues.Furthermore, you are interested in using and sharing your knowledge as part of your Internship in a modern working environment. Your further profile for this position:
- Reliable and accurate working style in a non-GMP environment
- Knowledge of Python and core data science libraries (such as OpenCV, scikit-learn, TensorFlow, or PyTorch) to build image processing pipelines
- Self-sufficient, problem solving-oriented work habits
- Good knowledge of MS-Office (Word, Excel, PowerPoint) and AI tools
- Proficiency in English, German is a plus
This internship opportunity is one of a number of positions we offer in the department per semester and isnot suitable for writing a Bachelor/Master/Diploma thesis.
The interviews will take place on an interview day with all considered candidates and representatives of the department.
Your complete application includes the following documents:
- A Current CV and a Motivation Letter
- A certificate of enrollment (if you are currently studying)
- For Non-EU/EFTA citizens: Due to regulations, you must provide a certificate issued by your university stating that an Internship is mandatory for your studies and you must be enrolled during the entire duration of the internship
- The RiSM task (see below)
Application process
The application deadline is23.08.2026. All successful final candidates will be invited to a virtual interview day which will take place on 14.10.2026.
The Internship will start in March to May 2027 and has a duration of6 months, please indicate your preferred start date in your application.
More information about the Roche Internship program in Synthetic Molecules (RiSM) and other opportunities within this program you can findhere.
Are you ready to apply? We are looking for someone who thinks beyond the job offered - someone who knows that this position can be a rare springboard to many other opportunities
Additional information (RiSM Task)
Assume you are a pharmaceutical data scientist tasked with identifying why different batches of a spray-dried amorphous solid dispersion (ASD) have a different compact/tableting performance, even though traditional laser diffraction analyses cannot discriminate between them.
What are your considerations with respect to setting up an image analysis pipeline, training a convolutional neural network (CNN) to generate a classification system, and correlating these findings with spray-drying process parameters to optimize drug product performance?
Please use the information provided in the following article (Hang Hu, Sampada Koranne, et al., "High-Speed Imaging-Based Particle Attribute Analysis of Spray-Dried Amorphous Solid Dispersions Using a Convolution Neural Network," Mol. Pharmaceutics 2025, 22, 488-497; https://doi.org/10.1021/acs.molpharmaceut.4c01092) to answer those questions.
We anticipate receiving your answers in the form of a slide deck suitable for presentation to a project team (maximum of 5 slides, PDF format) alongside your application.
Wer wir sind
Eine gesündere Zukunft treibt uns zur Innovation an. Mehr als 100.000 Mitarbeiter weltweit arbeiten gemeinsam daran, wissenschaftliche Fortschritte zu erzielen und sicherzustellen, dass jeder Zugang zur Gesundheitsversorgung hat – heute und für zukünftige Generationen. Durch unser Engagement werden über 26 Millionen Menschen mit unseren Medikamenten behandelt und mehr als 30 Milliarden Tests mit unseren Diagnostik-Produkten durchgeführt. Wir ermutigen uns gegenseitig, neue Möglichkeiten zu erkunden, Kreativität zu fördern und hohe Ziele zu setzen, um lebensverändernde Gesundheitslösungen zu liefern.
Gemeinsam können wir eine gesündere Zukunft gestalten.
Roche ist ein Arbeitgeber, der die Chancengleichheit fördert.
