47 computational-physics "https:" "https:" "https:" "https:" "University of Kent" Postdoctoral positions at Nature Careers in Germany
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Work group: Institute of Materials Physics Area of research: Scientific / postdoctoral posts Starting date: 23.12.2025 Job description: PostDoc at the P05 Nano-Tomography Endstation Job ID: 940
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natural and AI-designed protein domains, along with an engineered fusogenic protein. The technology has been recognized with the m4 Award, the GO-Bio next program, and is currently under revision in a top
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leftward flow in the left–right organizer (LRO), but the identity and mechanism of the flow-transported symmetry-breaking cue has long remained elusive. Defects in this process are a major cause of
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. Excellent communication and organizational skills and proficiency in English are mandatory. Proficiency in German is desirable. Application Process: Interested candidates should submit the following documents
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multidisciplinary environment of biologists, clinicians, computational scientists, and other colleagues within our research groups and with consortium partners of the FOR 5806 Your Profile We are looking for a self
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multidisciplinary environment of biologists, clinicians, computational scientists, and other colleagues within our research groups and with consortium partners of the FOR 5806 Your Profile We are looking for a self
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of motion analysis in collaboration processing of images in preparation for image-based modelling Your profile PhD in physics, materials science, computer science, applied mathematics or a related field
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transcriptomics programme to gain deeper insights into how different types of brain tumours grow and how brain tumour and brain resident cells interact in this process. You will contribute to these research efforts
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for image-based modelling Your profile PhD in physics, materials science, computer science, applied mathematics or a related field strong background in image processing and analysis, including deep learning
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The Microbiome Dynamics (MBD) department contributes, using computational methods, to the development of personalized microbiome-based strategies to aid in the detection, monitoring, treatment, and prevention