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-seq, GRO-seq, and RNA-seq. CRISPR genetic engineering. Rapid protein degradation using Degron system. Bioinformatics. Cardiac functional analyses. Mouse genetics. Lentivirus transduction. Cell culture
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the experimental data and the concepts of neuronal coding, and Elephant Analysis of the parallel rate data for submanifolds and their temporal dynamics during behavior Leverage dimensionality reduction and
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related in space and time and to behavioral events. Core Tasks: Getting familiar with the experimental data and the concepts of neuronal coding, and Elephant Analysis of the parallel rate data for
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Summary To perform scientific research, specifically research activities related to X-ray crystallography and bioinformatic analysis of proteins and to report results ready for publication and/or use
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strong background in applied mathematics Excellent programming skills (Python, C/C++) Good experience in machine learning and parallel computing Good organisational skills and ability to work both
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isotherm parameters directly from molecular properties. These predictions will be integrated into the open-source CADET simulation framework, enabling fully predictive process simulations without extensive
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of the recruitment and description of the project] * Background of the recruitment and description of the project The Human Information Engineering Lab, Department of Bioinformatics Engineering, Graduate School
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Learning about protein design and engineering Exploring cell-based and cell-free screening Applying high-throughput screening Utilizing bioinformatics, machine learning, and other computational approaches
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statistical genetic analyses. Ideally, you will also bring experience or training in areas such as medical statistics, UNIX systems, bioinformatics, or human genetics, though we welcome candidates eager
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experience in machine learning and parallel computing Good organisational skills and ability to work both independently and collaboratively Experience with deep learning frameworks, such as Tensorflow