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Your Job: You will work on the development of (meta)data extraction tools from electronic lab notebooks You will create tools for data transformation and integration from electronic lab notebooks
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research methods and statistics. - Experiences with research syntheses (e.g., meta-analyses) and video data analyses would be an advantage. - You have very good written and spoken Eng-lish skills and good
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developing a machine learning (ML) algorithm for the automated analysis of the above-mentioned mass spectra. Desirable: - knowledge in the field of Planetary Sciences - very good written and spoken English (C1
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an extensive safety analysis and calidation of perception algorithms in automotive. Through our work, we lay the foundation for a reliable digital future. What you will do In our Trustworthy Digital Health group
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assistance systems Collaboration in the development of AI algorithms (LLM, fine-tuning, RAG, AI agents, embeddings) Literature research on the topic of AI What you bring to the table Studies in
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- 20 hours per week. Key responsibilities: Support a systematic review and meta-analysis of quantitative ex-post evaluation literature in climate policy; Conduct structured searches using academic
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implementation, practical application, theoretical analysis and evaluation of AI algorithms Use of XAI tools to explain machine learning models Implementation of deep learning Improvement of models, e.g. in terms
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for technologies Conscientiousness in implementing, testing, and documenting algorithms Curiosity about a deeper understanding of deep Learning architectures Experience in academic writing is an advantage What you
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, and documenting algorithms High degree of proficiency in spoken and written English What you can expect Fascinating challenges in a scientific and entrepreneurial setting Attractive salary Modern and
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Master Thesis - Development of ligand conjugated lipid nanoparticles for targeted T cell delivery...
holistic view of interconnected biological systems in health and disease. We develop clearing technologies for cellular-level imaging and deep learning algorithms (AI) to analyze large imaging and molecular