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sequences, and to develop new methodology to predict conformational diversity and changes using machine learning. With the help of deep-learning approaches methods to predict flexibility, conformational
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, machine-learning, and integrative analyses of different -omics technologies (DNA, RNA, epigenetics) and image data analysis. Tasks include data analysis, method development, result summarization, project
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include the opportunity for three weeks of training in higher education teaching and learning. The fellow will be expected to lead/contribute to research linking vegetation modelling with the LPJ-GUESS
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at the Division of Computer Vision and Machine Learning (CVML) at the Centre for Mathematical Sciences . The Centre for Mathematical Sciences is a department affiliated with both the Faculty of Engineering (LTH
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primarily work with the analysis of large-scale data from DNA methylation arrays and SNP arrays, along with prospective clinical data. You will perform multiome analyzes and use machine learning methods
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. professional experience. Other assessment criteria: Experience working with Deep Learning and/or Computer Graphics Familiarity with Deep Learning and/or Computer Graphics research Interest in Computer Graphics
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research in the Humanities Lab in close collaboration with, and under the leadership of, professor Panos Athanasopoulos . There are currently around 15 linguistic PhDs and 6 PhD students employed by
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amounts of data from different sources. - Very good programming skills - Experience in applied AI and machine-learning methods. - Good knowledge of spoken and written Swedish. Research expertise is the
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work environment and committed employees. We have a strong focus on leading research and good teaching and we have access to equipment for advanced computer calculations and experimental measurements
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languages and program analysis Good knowledge of mathematics Interest in machine learning, especially LLMs Assessment criteria Selection for third-cycle studies is based on the student’s potential to profit