Working Student Chemoinformatics (all genders)
Working Student Chemoinformatics (all genders)
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Job Description
At Beiersdorf we want to help people feel good about their skin and our commitment goes far beyond caring for skin. For 140 years we have developed innovative skin and body care products for well-known brands such as NIVEA Eucerin La Prairie Hansaplast and Labello. We act according to our purpose WE CARE BEYOND SKIN and take responsibility for our consumers our employees the environment and society.
Behind every brand every product and every accomplishment are our more than 20000 employees. It is for them that we live an inclusive culture of respect and trust that is strongly aligned with our values CARE COURAGE SIMPLICITY and TRUST. We also embrace diversity by valuing the uniqueness of each individual and being committed to equal opportunities for all.
Your Tasks
We are seeking an enthusiastic and dedicated working student to join the Active Ingredients Discovery team at Beiersdorf. In this role you will support our research and development efforts by applying computational techniques to analyze chemical data develop predictive models and contribute to digital solutions for active ingredient discovery. This is a fantastic opportunity to gain hands-on experience in a dynamic interdisciplinary research environment. The position is limited to 20 hours per week for a minimum of one year.
The following tasks are part of your role:
- Execute ETL (Extract-Transform-Load) processes on chemical and biological datasets.
- Develop and validate cheminformatics workflows for compound screening and property prediction.
- Assist in implementing machine learning and cheminformatics algorithms for molecular modeling.
- Utilize cheminformatics toolkits (e.g. RDKit) and databases for data preprocessing.
- Troubleshoot and maintain IT infrastructure for computational chemistry platforms.
Your Profile
- Currently enrolled in a Bachelors or Masters program in Chemoinformatics Computational Chemistry Bioinformatics or a related field preferably in the 1st or 2nd semester.
- Strong programming skills in Python.
- Familiarity with cheminformatics tools (e.g. RDKit KNIME) and molecular modeling techniques.
- Analytical mindset with problem-solving abilities and attention to detail.
- Fluent in English; German is a plus but not required.
In case of any questions our recruiter Insa Koehnsen is available at.
Employment Type
Part-Time
