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., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted in the Department of Microbiome Dynamics of Prof. Gianni Panagiotou of the Leibniz-HKI in
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data Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will
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Introduction to Programming with Python Supervised Machine Learning Expected Qualifications: Minimum of a Master’s degree related to the area of teaching, with a preference for an earned doctorate (PhD or DBA
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. Desired: Degree with specialization in science or engineering preferred. Familiarity with Python and its management. Previous experience in both research and teaching laboratory settings, and experience
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Are you excited by the challenge of helping turn raw data and bold ideas into real-world AI systems? Do you thrive on fine-tuning models, writing clean Python and solving thorny technical problems
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. There are four scientific Divisions - Structural Studies, Protein and Nucleic Acid Chemistry, Cell Biology and Neurobiology. However, scientific collaboration between the different Divisions is extensive
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other empirical damage and vulnerability data. Couple the ABM with the Regional Flood Model (RFM) to describe temporal developments of flood risk considering adaptation decisions. Different adaptation
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uses. To investigate feature-level just-noticeable difference modelling for machines to facilitate assessment and optimization. To formulate a comprehensive visual feature codec for machine uses
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: · MATLAB · Python · ROS · Computer vision and/or YOLO · Pytorch and/or Tensor Flow · LiDAR · GIS · GNSS receivers Minimum Qualifications: Doctoral degree in Mechanical Engineering, Electrical Engineering, or
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regulatory environments, sustainability, or policy modeling in supply chains. Solid programming or modeling skills in tools such as Python. Strong analytical, writing, and communication skills in English. A