85 computational-physics-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL" PhD positions in Finland
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background in mechanics and computational engineering. Demonstrated interest in the physics of sea ice and computational modelling of ice will be considered as an advantage. Suitable backgrounds include
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. Demonstrated interest in the physics of sea ice and computational modelling of ice will be considered as an advantage. Suitable backgrounds include solid mechanics, mechanical engineering, computational
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Epitranscriptomic Regulation of Alternative Splicing for RNA Therapeutics Innovation ”. The EpiTheraRx project aims to develop computational approaches for identifying disease-relevant alternative splicing events
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Epitranscriptomic Regulation of Alternative Splicing for RNA Therapeutics Innovation ”. The EpiTheraRx project aims to develop computational approaches for identifying disease-relevant alternative splicing
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of DIESL (http://diesl.eu/), a multi-disciplinary research group that brings together diverse expertise in an open and constructive research environment. DIESL members study computational
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foundational topics in quantum computing and their practical applications. In this position, you will work at the intersection of quantum computing, computational biology, genomics, and materials
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academic performance in Mechanical Engineering, Technical Physics, or a closely related field. Additional studies or research experience in following will be considered an advantage: Computational
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categories Academic Discipline Physical Sciences , Physics & Astronomy Job Type Academic Posts , Postdocs , Research Related , Other Research Related Contract Type Fixed Term Hours Full Time Apply on
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candidates with a Master's degree in (computational) chemistry, physics, or materials science who are curious about applied machine learning in the natural sciences. Prior machine learning or Python
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, computational science, or closely related). Relevant coursework (examples): Computational physics/scientific computing and numerical methods for PDEs High‑performance computing (parallel distributed