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the information encoded in our genome to better diagnose, treat, predict and prevent disease. From the individual patient with rare diseases, to the many thousands affected by complex, widespread illness, we
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data. Together with the Artificial Intelligence and Cancer Evolution Division at the German Cancer Research Centre DKFZ, led by Moritz Gerstung, we have recently established a systematic spatial
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biogeochemical modelling and data-driven machine learning approaches at an ecosystem scale to improve our understanding of the fate of nitrogen fertilizers applied to agricultural soils. This understanding will be
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be developed and implemented in the GEOS-Chem chemical transport model, coupled to the Community Earth System Model. Standardized large wildfire events will be simulated based on historical data and
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Proteomics workflow. For more information: group.szbk.u-szeged.hu/sysbiol/horvath-peter-lab-index.html Your tasks Building large scale foundation models Applying and further developing single cell segmentation
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details of two referees to kaspar.valgepea@ut.ee by January 11, 2026 • Preferred start date: February 2026 • Work location: Institute of Bioengineering, Nooruse 1, Tartu For more information, contact group
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measurements A good understanding of advanced physiological techniques Experience with enzymatic in vitro assays and plant x climate interactions Experience in complex data handling and statistical analysis
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to join a collaborative, diverse, and creative research team. Experience in molecular biology, data analysis, and animal experiments is an advantage. The successful candidate will apply molecular and
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Are you interested in neuromorphic spintronic and can you contribute to the development of the project? Then the Department of Electrical and Computer Engineering invites you to apply for a one year
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increasing independence over time. Collaborate on project and analysis design guided by their PI. Develop new computational methods. Adhere to field and lab standards for data analysis. Identify, process