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, extract, and standardise functional information 2. Develop computational tools that integrate evolutionary and functional information using comparative genomics and deep learning approaches 3. Apply
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intelligence. Our research spans computer vision, machine learning, and natural language processing, focusing on multimodal learning, data fusion, spatial-temporal modeling, and vision–language models. We study
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-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus on implementing
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experimental studies, mechanistic modelling, time-resolved data analysis, and machine learning to develop and validate predictive models linking process signals to reaction behaviour, progressing from controlled
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of coverage metrics. Some other tasks: Preparing technical reports and scientific publications. Traveling to hospitals to acquire medical endoscopy video sequences. Traveling to attend conferences, consortium
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to learning Danish, including reading, writing, and speaking, is expected during the employment period. Contact Further information on the position may be obtained from Professor Margit Bak Jensen
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between Christmas and 1 January; multiple courses to follow from our Teaching and Learning Centre; multiple courses on topics such as leadership for academic staff; multiple courses on topics such as time
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learning or decision support applied to RF sensing, wireless communications and signal processing. A strong background in multimodal data analysis is expected, complemented by strong capacity for teamwork
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, you will design, train and implement ARCA: an AI foundation model for crop microbiomes. You will work at the interface of deep learning, bioinformatics and microbial ecology, using large-scale
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for deep learning, speech, and audio research, including Aalto University’s large-scale scientific computing cluster with CPU and GPU nodes, access to CSC’s national computing infrastructure including LUMI