- Ab-initio solubility prediction enhanced by machine learning
- General: Team-oriented and decision-making personality Problem solving-oriented work habits Good knowledge of MS-Office (Word, Excel, PowerPoint) & Google equivalents (gSheets, gDocs, gSlides) Proficient in English, German is a plus Experience working in a lab-environment.
- Specific for project area: Ab-initio solubility prediction enhanced by machine learning Good knowledge of python programming Basic knowledge of pandas, scikit-learn, XGBoost and Random forest regression models and hyperparameter tuning Basic knowledge of Jupyter Notebooks Ideally experience with Linux and Windows OS Ideally first experience with solid state characterization techniques: PXRD, DSC, TGA
- A Current CV and a Motivation Letter
- A certificate of enrollment (if you are currently studying). If you want to use this opportunity to do a Master's or Diploma thesis, please highlight this in your application
- 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
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Student Internships in Solid State Science for students enrolled in chemistry, chemical or process engineering, pharmacy, pharmaceutical sciences, pharmaceutical technology, or physics - Basel, Schweiz - Roche
Beschreibung
The Position
As part of the global technical development organization, the Particle Design group is the center of excellence for the design of drug substance particles with tailor-made solid-state properties to facilitate downstream processing to the drug product. This includes the development and optimization of the processes on laboratory scale, as well as scale-up of the corresponding manufacturing processes in close collaboration with the production sites. Our responsibilities also include the evaluation and implementation of new strategies to obtain particles with the desired properties.
As an Intern in the particle design group you will be working on the following project-area:
Improvement of the already established workflow for the solubility computation by a machine-learning module. This includes an experimental part (70% laboratory work including sample preparation, solubility measurements and solid residue analysis) as well as a computational part: The remaining 30% will be dedicated to data preparation, model training and evaluation of different machine learning models.
Who you are
You are an enrolled student in the subject of chemistry, chemical or process engineering, pharmacy, pharmaceutical sciences, pharmaceutical technology, physics or a related field (preferably with a bachelor's degree) and have an interest and experience in crystallization and solid-state characterization. Furthermore, you are interested in using and sharing your knowledge as part of a 6-12 months internship in a modern working environment.
Your further profile for one of the positions:
Your complete application includes the following documents
Application Process
The Internship willstart in 2024 for 6-12 month, please indicate your preferred start date and durationin your application.
More information about theRoche Internship program in Synthetic Molecules(RiSM) and other opportunities within this program you can findhere.
Roche embraces diversity and equal opportunity in a serious way. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better our work will be.
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
