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at Aalto University (https://into.aalto.fi/display/endoctoralsci/How+to+apply#Howtoapply-Eli… ) a Master’s degree in Artificial Intelligence, Machine Learning, Computer Science, Cognitive Science
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of results Completing the required PhD school courses and conducting an external research stay Teaching and supervision of MSc students Desired qualifications and skills: Curiosity and high motivation
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from visual and auditory cortices recorded over multiple days Apply and adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural
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Are you fascinated by understanding fundamental neurobiological processes in the context of stress and depression? Are you intrigued to learn more about early-life stress as risk factor for
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or for multiobjective optimization problems. Implement the developed algorithms (e.g., in Python) and evaluate their practical performance on artificial and/or real-world data. Teach tutorials (in English) for
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Solid experience with statistical modeling, machine learning, or AI Practical skills in R and/or Python for data analysis and model development Familiarity with microbial ecology, genomics, or food safety
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used will be Density Functional Theory, statistics, machine-learning and dynamics. Collaboration with members of other research groups at UCPH and abroad is required. Who are we looking for? We
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and presenting research ideas and results. Education & work experience · Basic: Msc. in environmental sciences, ecological economics or environmental engineering. · Education or proven
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machine learning methods to investigate how ecosystem water stress and drought disturbances affect relevant forest ecosystem functioning at various scales. It will enable advanced assessment of forest
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comparative and statistical approaches Exploring evolutionary hypotheses by clustering behavioural traits and mapping them onto phylogenetic trees Collaborating with a multidisciplinary team of biomechanists