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The Department of Food Science, Aarhus University (Denmark), invites applications for a 36-month postdoc position to work the physical chemistry of food proteins, in particular their structure
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. Enthusiastic candidates with a strong background in molecular/cellular biology, biochemistry, immunology, and/or related field are encouraged to apply. The successful candidate will lead a cross-disciplinary
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this model with experimental data, you will uncover how RNA-binding proteins “read” this tag to determine the mRNA’s fate. This exciting work connects molecular biology and mathematical modeling, and helps
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, physics, mathematics, computer science, or related fields Demonstrated hands-on experience with machine learning techniques Strong programming skills (Python preferred) Experience analyzing time-series data
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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Lightweight and flexible solar cells Space deployable structures Device analysis in space environments Big data, AI, and machine learning for space solar initiatives Recruitment Attract top-tier postdoctoral
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of these patients. The goal of this project is to combine cutting-edge multi-omics technology, data analytics, machine learning and clinical samples from the human eye to decipher new insights into disease mechanisms
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is connected to the vibrant local ecosystem for data science, machine learning and computational biology in Heidelberg (including ELLIS Life Heidelberg and the AI Health Innovation Cluster ). Your
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Postdoctoral researcher in Environmental Analytical Chemistry, with a focus on non-target screeni...
, environmental or food) chemistry or a closely related discipline. The candidate should have experience with non-target screening (or metabolomics) of environmental contaminants and related data analysis, have
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Do you have a computational background and interest in developing novel tools for integrating structural biology data to understand regulation of disordered regions of proteins? Then the Viennet lab