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-engineering-and-automation/nonlinear-systems-and-control ) at Aalto University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees
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in this project. Additionally, the student will be encouraged to collaboratively contribute to the further development of these methods. The PhD student will be supervised by Academy Fellow Dr. Gleb
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bioinformatics Communicating the results in scientific publications and conference presentation Co-supervising PhD and MSc students working in the project Contributing to new research ideas and (co)-applying
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chemical activation method, and develop environmentally friendly electrolytes. Work will focus on: Preparation, characterization, and optimization of porous carbon electrode ink for supercapacitor
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to polarization. Leveraging network science, NLP, behavioral sensing, and causal inference, the project pioneers new methods for detecting and mitigating online harms. Its results aim to inform public health
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characterization of the deposited materials. The mechanical resilience of the deposited materials is studied using application-relevant standardized methods such as bending, scratching and nanoindentation. The ENS
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software (e.g., NVivo, Atlas.ti). The applicant benefits from previous experience or interest with digital research methods, online ethnography, or youth-focused research. Excellent interpersonal skills and
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methods and relevant software (e.g., NVivo, Atlas.ti). The applicant benefits from previous experience or interest with digital research methods, online ethnography, or youth-focused research. Excellent
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molecular biology methods, such as cell culture models, reporter assays, and NGS-based techniques, to investigate the mechanisms and errors associated with somatic hypermutation. The research group is located
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, scientific rigor, and innovation. We work in close collaboration with clinicians and other experts in molecular virology, immunology, genomics, and bioinformatics. Qualifications PhD (completed or near