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samples, lack of training data and sample variability. In this project we aim to develop AI/ML workflows for improved quantitative analysis of LNPs. Your responsibilities will include optimisation of data
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molecular biology, comprising millions of images and extensive molecular measurements. All data are released openly and widely used by researchers worldwide. The Alpha Cell program is recruiting a
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), statistical analysis of LHC data or beyond-the-Standard-Model phenomenology, is meriting. Experience with large-scale training on GPU and HPC systems, with design of experiments and active learning, with open
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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from molecular dynamics simulation trajectories in silico. On the wet-lab side, the position involves generating both fluorescence and mass spectrometry data and optimizing protocols for its analysis
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an outstanding and ambitious postdoctoral researcher in computational biology to pioneer understanding and modeling of tissue architecture using single-cell and spatial transcriptomics data. The focus will be
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microscopy, image analysis: Development of microscopes, fluidics, and data analysis pipelines used to acquire and quantify high-throughput binding data. Examples of suitable backgrounds: Optical engineering
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existing genomic datasets and enable analysis of gene regulation at cell-type resolution. The project places particular emphasis on ensuring high data quality and developing robust methods that can be
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studies for one year, with a possibility of prolongation. Start date in September or as per agreement. Additional information Further information about the project and about the conditions of
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Systems and Software Program (WASP ). You can find more information about us on the Department of Information Technology website. The position is hosted by the Division of Scientific Computing (TDB), one