230 structures-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" positions at Nature Careers
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dynamics, kinematics, acoustics/vibrations, fluid–structure interaction, control, or other mechanics-driven domains. Experience with applied computational methods and machine-learning–based modeling
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the complex structure of populations into single-cell components that can be studied individually and collectively. To achieve this, we will apply novel tools based on semi-permeable capsules, including various
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. To help us build on the success of the portfolio, we’re seeking an editor with experience in computational biology, bioinformatics and systems biology (genome informatics and/or computational structural
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students. The department is responsible for two educations: Molecular Biology and Molecular Medicine with a yearly uptake of 160 students in total. Please refer to http://mbg.au.dk/ for further information
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seeking an editor with experience in computational biology, bioinformatics and systems biology (genome informatics and/or computational structural biology preferred) who has a critical eye, a deep
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creative approaches for completing work while promoting balance between work and personal commitments. These approaches involve use of non-traditional work hours, locations, and/or job structures. Penn Home
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vitae (max. 3 pages), structured as per TENK guidelines completing the sections relevant for applicant’s career stage and the target position. Two reference letters submitted by the referees via
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, multiplex imaging) Model spatial cellular organization, tissue architecture, and microenvironmental interactions Design multi-scale models of tissue structure, function, and disease progression Collaborate
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and in scientific publishing Basic experience in research methods and academic writing Knowledge of university processes and structures Experience in remote teaching using modern IT infrastructures What
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sequence analysis Single cell analysis Protein structure prediction Cancer multiomics analysis Genotype to phenotype mapping You are expected to contribute to strengthen the deep learning focus