Network Analysis and Modelling group offers MSc projects cantered on plant genomics and cutting-edge machine learning. We're inviting ambitious students to join us to develop algorithms bridging meta- and quantitative-data in the NGS experiments. This project presents a unique opportunity to develop and refine your skills in constructing deep learning models and acquire experience with NGS data. We welcome students with background in bioinformatics or data science and good programming skills. The positions concerns students who want to complete ther MSc Thesis with us.

Your tasks:

• Assemble and analyze large-scale RNA-seq datasets
• Build interpretable deep learning models
• Critically evaluate model performance and biological implications
• Document and share your workflows
• Report your work in oral presentations

Your qualifications and skills:

• Good programming skills in python and/or R
• Some experience with linux
• Some experience with pandas, tensorflow, scikit-learn is desirable
• Basic understanding of molecular biology

You fit to us:

• You have a strong interest in bioinformatics and machine learning.
• You have good communication skills.
• You aim to work independently, take initiative, and solve problems.

We offer you:

• Access to high-performance computing infrastructure
• Work under competent supervision
• Employment as a research assistant (f/m/d) for up to 6 months
• Accommodation in the IPK guest house (on request)
• Possibility to work remotely

If you have any questions and would like to know more about current projects, please contact: Dr. Jedrzej Szymanski (email: szymanski@ipk-gatersleben.de, tel.: +49 39482 5753) or Fritz Peleke  (peleke@ipk-gatersleben.de, tel.: +49 39482 5829).