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of Information Technology, and will be conducted alongside other researchers at the Centre for image Analysis who develop computational methods with a particularfocus on deep learning and image analysis. The project relies
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breakthroughs in deep learning–powered protein design, recognized by the 2024 Nobel Prize in Chemistry, have enabled the creation of proteins with near-atomic accuracy. Models such as RFdiffusion, LigandMPNN, and
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will work with tools such as AlphaFold and RosettaFold-diffusion and apply deep learning to address the next challenges in dynamics and the design of novel protein-based therapeutics. As postdoc, you
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. Significant experience of developing deep learning methods using computational frameworks such as PyTorch, TensorFlow etc. Experience of working with molecular questions in the biosciences An interest and
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employment decision is made. Doctoral degree in remote sensing, geoinformatics, computer science, or a closely related field. You have experience developing and applying deep learning models for Earth
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military service. The following experience will strengthen your application: Experience of working with modern deep learning frameworks and large language models, Experience in any of the three priority
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biomedical sciences. Experience with sequencing data preprocessing, RNA splicing, deep learning and analysis of human multi-omics data is an advantage. The candidate should exhibit a high degree of
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data preprocessing, RNA splicing, deep learning and analysis of human multi-omics data is an advantage. The candidate should exhibit a high degree of independence but on the other hand also value a
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, correct batch effects, and preserve biologically meaningful signals. Clinical contextualization: acquire a deep understanding of breast‑cancer pathology and treatment pathways to evaluate how integrated
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degree. This eligibility requirement must be met no later than the time the employment decision is made. PhD in Railway Engineering, Civil Engineering, Geotechnical Engineering, or a closely related field