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collaborations, we are a key force in the field. Our core competencies include in vitro ADME models, advanced in vivo methods, computational modeling and simulation, as well as patient-focused and policy-related
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field observations and interviews. Analysis using qualitative social science methods. Active participation in project workshops, meetings and public engagement activities. Qualification requirements
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molecular simulations. Previous hands-on experience in more than one of the following methods is considered an advantage: molecular simulations, Python programming, machine learning, or quantitative analysis
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parallel to what has recently been shown in human gut health, microbial diversity on both leaves and roots is an important factor in overall plant health. However, the connections between plant disease and
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: https://wasp-sweden.org/ Project description Trustworthy machine learning is an umbrella term that provides methods and tools to ensure that AI and ML systems are verifiable, robust, secure, privacy
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factor in the design of the project. The project and research environment will give the dedicated student the opportunity to train as a first-class researcher. A person who is employed as a PhD student
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Trustworthy machine learning is an umbrella term that provides methods and tools to ensure that AI and ML systems are verifiable, robust, secure, privacy-preserving, and ethical, which leads to greater adoption
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leaves and roots is an important factor in overall plant health. However, the connections between plant disease and plant-associated microbial communities are not well known. Prevalent plant pathology
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basic eligibility requirements for third-cycle studies in applied economics. Candidates must demonstrate knowledge of research methods in applied or agricultural and food economics, as well as strong
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the electronic properties of organic semiconductors through light-driven chemical doping. The work will involve combining tailored materials design with advanced characterization methods to enable new device