210 structures-"https:"-"https:"-"https:"-"https:"-"https:"-"FCiências" positions in Norway
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++ dealing with physical problems in fluid mechanics is an advantage. Applicants must be able to work independently and in a structured manner and have the ability to cooperate with others. Applicants must
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, Python, C/C++ dealing with physical problems in fluid mechanics is an advantage. Applicants must be able to work independently and in a structured manner and have the ability to cooperate with others
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cohort data to investigate how social structures interact with individual and family-level risk factors to influence life-course trajectories. Within this framework, the successful candidate will focus
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perspectives Proficiency in written and oral English Good knowledge of Norwegian language is an advantage Demonstrated ability to work independently in a structured manner, while also possessing strong
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of their master’s degree are also encouraged to apply. Personal qualities Personal characteristics work independently, but also participate in teamwork work in a structured way set goals and make plans to achieve
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. Experience in the construction or application of empirical or semi-empirical models of time-variable stellar irradiation. Familiarity with the high-energy environments of young stars and their impact on
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embryonic development, leveraging our state-of-the-art epigenetic and epitranscriptomic methodologies (Nature, 2016; Nature Genetics, 2020; Nature Structural & Molecular Biology, 2023; Nature Biotechnology
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conditions is an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good collaborative skills. Applicants must have good written and oral English skills
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must be able to work independently and in a structured manner, and demonstrate both initiative and good collaborative skills. Applicants must have good written and oral English skills Personal and
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in English Solid knowledge in finite element analysis (FEA) and strong skills in FEA software such as ABAQUS Hands-on experience in the construction and application of deep learning neural networks