Join a multi-disciplinary team to contribute in both technical and scientific aspects at the interface between biology, chemistry and machine learning; Participate in research projects involving cutting-edge therapeutical strategies such as gene-therapy, targeted protein degradation and other groundbreaking developments of enormous potential; Innovate through the application, development, and integration of state-of-the-art deep learning models to further understand relevant biomolecular interactions with a strong emphasis on interpretability at the molecular structure level
Requirements:
PhD in a relevant discipline, such as biochemistry, computer science, biophysics or related fields, accompanied by original research publications. Additional industry or postdoctoral research experience will be valued very positively; Expertise in scripting/programming (e.g. R, Python, C++), data analysis and biological interpretation regarding molecular data (e.g. protein 3D structures, sequence, compound SMILES, etc); Experience in applying or developing machine/deep learning models in the context of 3D macromolecular structures (CNNs, VAEs, graphs, etc), ideally considering aspects of molecular flexibility, dynamics and conformational change
Text:
Senior Scientist - Structural Bioinformatics Research Join a multi-disciplinary team to contribute in both technical and scientific aspects at the interface between biology, chemistry and machine learning; Participate in research projects involving cutting-edge therapeutical strategies such as gene-therapy, targeted protein degradation and other groundbreaking developments of enormous potential; Innovate through the application, development, and integration of state-of-the-art deep learning models to further understand relevant biomolecular interactions with a strong emphasis on interpretability at the molecular structure level PhD in a relevant discipline, such as biochemistry, computer science, biophysics or related fields, accompanied by original research publications. Additional industry or postdoctoral research experience will be valued very positively; Expertise in scripting/programming (e.g. R, Python, C++), data analysis and biological interpretation regarding molecular data (e.g. protein 3D structures, sequence, compound SMILES, etc); Experience in applying or developing machine/deep learning models in the context of 3D macromolecular structures (CNNs, VAEs, graphs, etc), ideally considering aspects of molecular flexibility, dynamics and conformational change
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