507 machine-learning "https:" "https:" "https:" "The University of Edinburgh" PhD positions in Germany
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The analysis of generated data and communication within an interdisciplinary team made up of people working in natural, life and computer sciences as well as medicine Presenting the research outcome in lab
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well as basic research with the combined tools of immunology, microbiology, virology, cell biology and molecular biology. For more information, please see https://www.mhh.de/hbrs/zib MD/PhD Molecular Medicine:The
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), the sorption of PFAS and heavy metals onto natural nanoparticles will be investigated in situ using a dedicated field exposure method developed by our team, complemented by laboratory experiments and machine
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more than 42,000 employees and an annual budget of over € 5 billion, the Helmholtz Association is Germany's largest scientific organisation. Where to apply E-mail jill.lewandowski@dzne.de Website https
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scientific organisation. Where to apply E-mail personal@ufz.de Website https://recruitingapp-5128.de.umantis.com/Vacancies/3370/Description/2 Requirements Additional Information Website for additional job
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Degree Dr rer nat Course location München In cooperation with Find out about the participating research groups here: https://www.lsm.bio.lmu.de/faculty/current-members/index.html Teaching language
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natural sciences (http://www.gauss.uni-goettingen.de ). The Faculty of Physics offers you a wide range of physical sub-fields such as the following: astrophysics biophysics geophysics materials physics
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for building a career in academia or industry Professional development through JuDocS, including training courses, networking, and structured continuing education ( https://www.fz-juelich.de/en/judocs
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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | 2 months ago
applicant has a strong background in bioinformatics and/or probabilistic machine learning, as well as experience in omics data analysis, and possesses solid English-language skills. Experience with
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for improved understanding of structural and kinetic processes in electrolytes; and machine learning concepts for improved analysis of experimental and simulated data. Material Synthesis Within this research