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Data Scientist
vor 2 Wochen
Tasks
- Develop and optimize ML models: Design, train, and fine-tune machine learning models (e.g. GNNs, deep neural networks, protein language models) to predict and design protein-protein interactions, such as antibody-antigen and TCR-peptide binding.
- Collaboration with experimental team: Interact closely with laboratory scientists to incorporate experimental feedback. Plan in silico experiments in tandem with wet-lab validation - for example, use experimental binding or structural data to improve models, and suggest new designs for lab testing.
- Research and innovation: Stay up-to-date with the latest computational immunology and protein design research. Prototype novel approaches (such as protein language models, diffusion models, or improved GNN architectures) and assess their potential to enhance the DeepIR design platform.
- Communication: Present findings and progress in team meetings. Contribute to publications or reports as needed, clearly communicating complex computational results to interdisciplinary team members.
**Requirements**:
- Education & Experience: Master’s degree or PhD in Data Science, Computer Science, Computational Biology, Bioinformatics, or a related field. 0-4 years of relevant experience (industry or research).
- Machine Learning Expertise: Hands-on experience with machine learning/deep learning, including proficiency in Python and libraries such as PyTorch or TensorFlow. Ability to develop and debug models and data pipelines.
- Graph Neural Networks: Familiarity with graph-based learning techniques. Ideally experience using GNN frameworks (e.g. PyTorch Geometric, DGL) for structural biology or network data, and understanding of how GNNs can model molecular interactions.
- Computational Biology Knowledge: Basic understanding of protein biology and structural modeling (e.g. concepts of antibodies, TCRs, amino acid properties, PDB files). Experience in handling biological datasets or working on problems like protein structure prediction, molecular dynamics, or sequence analysis.
At BIIE, you will be an integral part of a mission to accelerate immunology breakthroughs. This role offers the opportunity to shape how cutting-edge research data is captured and utilized, by building a digital foundation for our labs. You will work in a highly collaborative and interdisciplinary setting. We offer a competitive salary and benefits package, opportunities for professional development (including Benchling certification programs), and the chance to make a tangible impact on scientific discovery by empowering researchers with effective technology.
