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is looking for a postdoctoral researcher, doctoral researcher or project researcher to develop machine learning methods for health data analytics. The fixed term position starts on mutual agreement
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omics datasets developing and applying machine learning methods to biomedical questions keeping up with rapidly evolving methods in the field collaborating with biomedical researchers to assess
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in software engineering, machine learning, artificial intelligence, and human-computer interaction, the Unit provides a strong foundation and supportive environment for doctoral studies. In
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learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted drug design” is led by Docent Juri Timonen
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integrated circuit design. Possible focus areas can include, but are not limited to, machine learning (ML), Artificial Intelligence (AI), neuromorphic computing, and digital signal processing hardware
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: neuromorphic algorithms, machine learning, classifier development, AI programming Key tasks include experimental and/or computational research, collaboration within the project team, publishing results in high
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, PyTorch, Keras, scikit-learn) and strong understanding of machine learning algorithms, deep learning architectures, and statistical methods Good skills in extraction of data from structured/unstructured
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, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and
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at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks
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experimentation to develop integrative metamodeling approaches, qualitative systems analysis methods and causal graph-based solutions for machine learning. The team aims to advance innovative and robust solutions