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on developing novel Machine Learning methods for financial markets. The positions will offer excellent opportunities to work in a team of professionals responsible for developing cutting-edge technologies in
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edges in technology, health and society. www.tuni.fi/en Job Description Project title: Develop methods to assess the neuronal system (brain) state and the effect of the spatiotemporally steered stimulation
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Doctoral Researchers (PhD students) to work on deep learning methodologies for machine and robot perception. These positions are funded by the Horizon Europe project OPERA (Open Perception, Learning, and
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Dynamics, Mechanisms, Sensitivity, Specificity, Single-cell Variability, and Vulnerabilities. Our group is multi-disciplinary, combining methods from Bioinformatics (RNA-seq, biological databases
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reproducible computational pipelines, preferably with workflow management systems like Snakemake, Ability to containerize applications using Docker, Singularity, Apptainer for better software management and
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interface materials and bonding parameters for individual GaN chips. Characterize the bonded samples using mechanical, electrical, and thermal analysis methods to assess bonding quality and identify
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multiphysics approaches and ionic in-body communication instantiated by dedicated microelectronic hardware. Preclinical in-vitro and in-vivo testing of devices and methods will allow real world validation
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methods and software development. The objective of the Unit is to balance basic and industrially applicable research, having both performed with excellence in each of the research areas. The positions will
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for a Doctoral Researcher (PhD student) to work on visual studies, design and user experience related to screen interfaces. This research is part of a project funded by the Academy of Finland called
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doctoral researcher for PhD studies on liquid crystal elastomers within the framework of the ERC Consolidator Grant project Multimodal Sensory-Motorized Material Systems (MULTIMODAL) . The SPM group focuses