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for genomics (e.g., generative models, transformers, agentic workflows) and/or statistical learning (e.g., network & spatiotemporal modeling, functional/longitudinal data, time-series). Analyze single-cell
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. The scientific objectives include constraining cosmological and astrophysical models, extracting information from small scales through SBI, both as standalone probes and in combination. More specifically, the
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the chance to participate actively in staff trainings and development projects based on your interests and needs. We value work-life balance and well-being in all aspects of life. We work in a hybrid model
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modeling and techno-economic assessment as appropriate. The candidate will work independently under general guidance, collaborate effectively within a multidisciplinary team environment, and prepare
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, Medical Statistics, Mathematics or similar. The candidate should have a strong background in second-generation sequencing analyses (RNA) with focus on circRNAs, pathways analyses and biomarker discovery
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, Mathematics, or closely related fields. • Experience conducting experimental, theoretical, or computational research. • Familiarity with mathematical modeling, data analysis techniques, or computational tools
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the holistic understanding of space and its broader societal, ethical, and environmental impacts. Through responsible, multi-disciplinary research, including novel sensors, environment modelling
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care for patients requiring urgent or emergent intervention. The fellowship provides comprehensive training in data engineering, exploratory analysis, statistical modeling, machine learning, and artificial
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challenges in stem cell research, aging and disease modeling. The group employs methodologies from different areas of mathematics, engineering, and physics, and integrates multiple sources of biological
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the holistic understanding of space and its broader societal, ethical, and environmental impacts. Through responsible, multi-disciplinary research, including novel sensors, environment modelling