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advanced machine learning methods for multimodal and 3D medical image analysis in musculoskeletal medicine, in close collaboration with clinicians and computer scientists. PhD or Postdoctoral Researcher
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consideration, the application should include a cover letter, a detailed CV, a brief statement of your research experiences and interests, relevant certificates, and the names and contact information of two
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Max Planck Institute for Evolutionary Biology, Plön | Plon, Schleswig Holstein | Germany | about 1 month ago
complex traits. We take a multidisciplinary approach, integrating temporal genomic and high-throughput phenotypic data from experimental evolution in highly replicated Drosophila populations with
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analysis of NGS data (ChIP-seq, CUT&Tag, RNA-seq, ATAC-seq) Demonstrated ability in writing scientific reports and papers Proficiency with MS Office, graphic programs (Illustrator, ImageJ), statistical
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of sintered structures Structured storage of research data in the electronic laboratory notebook Preparation of publications, participation in conferences Supervision of students Your qualifications
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processing methods, mechanistic computer models and software tools and to use them in highly relevant clinical, biotechnological and pharmaceutical applications at the forefront of research. All projects
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computer language (Python or related) hands-on experience with instrumentation development excellent oral and written English skills collaborative mindset Skills and knowledge considered as assets: working
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influenced corrosion (MIC) in marine environments. It uses AI-supported models, Bayesian data fusion, and real-time sensor data integration. Your responsibilities include: Development of a digital twin (DT
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publications, diplomas, a two-page research proposal and contact information of two persons who can provide a reference letter. Please send your application electronically (one pdf-document
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production of survey data, as well as in the analysis and publications produced in this context. Job description: • Theoretical and data-based scientific contributions on the relationship between attitudes