57 linked-data-"https:" "https:" "https:" "Technical University Of Denmark" positions at SciLifeLab
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university. More information about us, please visit: the Department of Biochemistry and Biophysics . Project description Project title: Perturbation-based Multi-omics Inference of Gene Regulatory Networks
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Troubleshoot experimental procedures and improve robustness and reproducibility Document experiments and manage data in a structured and reproducible manner Collaborate with experimental and computational team
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-how in molecular biosciences. NBIS is also the Swedish node in the European infrastructure ELIXIR for biological information. We are now strengthening our capacity in our NBIS support unit for cell and
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recruiting an outstanding and ambitious postdoctoral researcher in computational biology to advance the integration and modeling of large-scale microscopy data using modern machine learning approaches
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information about us, please visit: www.dbb.su.se . Main responsibilities We are looking for a highly motivated staff scientist to join the In Situ Sequencing (ISS). While formally affiliated with DBB
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university. More information about us, please visit: the Department of Biochemistry and Biophysics . Project description Project title: Perturbation-based Multi-omics Inference of Gene Regulatory Networks
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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep
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at KTH in the Biotechnology doctoral program (according to KTH’s regulations). Signing a researcher agreement is a necessary condition to accept this PhD position. More information about Formulation of
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includes a combination of experimental work, data analysis, as well as interpretation and presentation of research results. The main part of the work for the advertised position involves studies of specific
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information about us, please visit: www.dbb.su.se . Project description The candidate will develop machine learning (ML) strategies, primarily revolving around interpretable ML and generative AI, to study