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GWAS software (e.g., GEMMA, EMMAX, GAPIT, FarmCPU, BLINK). Ability to run mixed linear models, handle covariates, correct for population structure/kinship, and perform quality filtering of SNP data
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be used to prepare lamella samples for high resolution cryo-EM imaging and tomography. From AI assisted image analysis, 3D models for key proteins and biomolecular complexes will be fitted into 3D
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or similar. Experience in handling dynamic modelling and control, experimental setup and testing, Digital Twin and Machine Learning Publication experience Collaboration and/or management skills Communication
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microscopy, optical interferometry, vacuum technology, finite element method simulations will be involved. Applicants should hold a PhD in Physics, Nano-science, Engineering or similar, experience with optics
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2026 or as soon as possible thereafter. The Post Doc will be connected to ongoing research activities conducted within the area of Sensory and Consumer Science. The candidate is also expected to take
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ecological data collection. The positions focus on improving detection and classification performance of deep learning models applied to millions of images collected in European monitoring programs. Key
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dynamics information. As a postdoc, you will contribute to the development of single molecule fluorescence real-time imaging methodologies using both experimental approaches, involving model nucleic acids
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such as multi-level models, target trail emulation, mediation analysis and g-computation Supervision of bachelors’ and masters’ students You will report to Professor Christina C. Dahm. Your competences You
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modeling. The position is available from 1 May 2026 or as soon as possible hereafter. Job description/research area The postdoc will contribute to a project enhancing cross-disciplinary collaboration by
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research project The project will address distinct metabolic pathways in prostate cancer progression. The study is based on an in vivo CRISPR mouse model for prostate cancer, introducing multiple mutations