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environment project, we will develop automated species and community recognition, particularly focusing on pathogenic soil fungi, with help of deep-learning algorithms fed with microscopic image and Raman
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includes signal processing with emphasis on development and optimization of algorithms for processing single and multi-dimensional signals that are closely related to applications and applied research
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focusing on herring in the Baltic Sea and will collaborate closely with several researchers at the Department of Aquatic Resources. The postdoc is expected to engage actively across multiple levels
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in their computation. We want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several
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collaborate with multiple stakeholders and conduct applied research in silviculture, forest ecology, pathology, policy and planning. We teach bachelor, Masters and PhD level courses addressing all
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algorithms. Work duties The main duties involved in a post-doctoral position is to conduct research. Teaching may also be included, but up to no more than 20% of working hours. The position includes
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the following is required and should be clearly described in the personal letter: Protein expression in various prokaryotes and/or yeasts Experience with multiple protein purification techniques Development
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particular expression with unspecified matrix sizes. When a concrete expression is evaluated at run-time, thus revealing the matrix sizes, an extraction algorithm can identify an optimal evaluation scheme
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mathematics, ecology, history, climatic and medical sciences in collaboration across multiple institutes. An integral part of the project is to develop process-based eco-epidemiological models considering
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spinal cord as a model system. You will engage a systematic strategy to identify these mechanisms by generating innovative mouse genetic strains, identifying embryonic defects and the underlying molecular