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experience with building Docker containers. Experience with high-throughput sequencing data analysis (e.g., CAGE, ATAC-seq, ChIP-seq, or Hi-C). Familiarity with epigenetics, gene regulation, or chromatin
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on interdisciplinary research focused on maternal and infant health. We are open to a range of experience and training: successful candidates might have a master’s degree and years of experience in analysis of health
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environment. The candidate will take part in the larger Cosmoglobe project aiming to do joint end-to-end analysis of a wide range of cosmological datasets, including archival data such as AKARI, DIRBE, FIRAS
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the start date. This position is part of the research project “Numerical Analysis of Stochastic TRANsport” (NASTRAN), funded by the Research Council of Norway. The project’s goal is to develop mathematical
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for analysis of Hi-C (or related) data Fluent oral and written communication skills in English. Desired qualifications: Experience with software and/or pipeline development (using e.g. Python, C++, or similar
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high-throughput sequencing data analysis (e.g., CAGE, ATAC-seq, ChIP-seq, or Hi-C) Expertise in statistical modeling for biological data Knowledge of enhancer-promoter interactions and 3D genome
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well as data analysis of large-scale registry data comparing mutation carriers to non-carriers. The aim of the project is to generate novel insights into human endogenous opioid function. The project offers
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implementing Molecularly Imprinted Polymers (MIPs) in the sample preparation workflow of bottom-up liquid chromatography-mass spectrometry (LC-MS) analysis of established disease biomarkers. Novel MIP-assays
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of Oslo. We seek a highly motivated postdoctoral candidate with experience in (i) conducting behavioural assays, (ii) performing electrophysiological recordings, and (iii) analysis neuronal data, including
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set to begin on February 1, 2026, although there is some flexibility in the start date. This position is part of the research project “Numerical Analysis of Stochastic TRANsport” (NASTRAN), funded by