304 phd-computer-science-"IMPRS-ML"-"IMPRS-ML" Postdoctoral positions at Nature Careers
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Systems Engineering, Computer Science, Software Engineering, Mathematics, or a related field Experience with interdisciplinary, multidisciplinary, or transdisciplinary research projects and related research
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schizophrenia. Preference will be given to applicants who have received their Ph.D. degrees in computational neuroscience, physics, mathematics, computer science, or related fields within the last 3 years and
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computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and
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regenerative medicine. Duties The field of synthetic biology is highly interdisciplinary, combining advanced molecular tools (e.g., CRISPR-based genome engineering), computational algorithms, and DNA/RNA
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The team you will be working with: Maxime Cordy Mike Papadakis Your profile A PhD in Computer Science, Software Engineering, Programming Languages or related disciplines. Documented research expertise in
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scientific areas. We educate both Bachelors and Masters of Science in Engineering and around 825 students are enrolled in our study programs. Furthermore, we also offer an ambitious PhD program. Our PhD
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. Your profile: PhD in synthetic biology, natural product chemistry, microbiology, life science, or a related discipline Extensive experience in synthetic biology and molecular biology techniques
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physical sciences, engineering, advanced microscopy techniques, and DNA nanotechnology. Biochemists, synthetic biologists, bioengineers, chemical biologists, chemists, or candidates with a computational
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immunotherapies for pediatric tumors. Studies are focused on using genetic engineering approaches to not only render immune cells cancer specific, but also improve their effector function. Genetically modified
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the program will receive training in genomic analysis, experimental modeling, translational science, and preclinical modeling of childhood hematological malignancies. The training program will equip the next