20 programming-language-"Data-driven-Materials-Modeling" PhD positions at Umeå University
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programme. The programme comprises 25 credits and is offered at two study rates: 25 credits over eight semesters, corresponding to four years of full-time study, or over twelve semesters, corresponding to six
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coursework in probability theory, programming, and linear algebra. be able to read and write mathematical proofs and cryptographic analyses. be proficient in academic English. For directions 1 and 3, it is
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PhD position in Experimental Physics with focus on photonics and materials science (applied aspects)
, or equivalent, in physics, applied physics, optics/photonics, nanoscience, materials science, electrical engineering, or a closely related field. Fluency in English is mandatory. A documented
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, nanoscience, electrical engineering, or a closely related field. English fluency, both written and spoken, is mandatory. A documented background in photonics, nanophotonics, ultrafast optics, condensed matter
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well as good knowledge in written and spoken English is a requirement. Merits are: Experience with environmental data analysis and quantitative methods, with programming experience in one or more languages such
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programming experience in one or more languages such as Python, R, or MATLAB. Experience working with marine / environmental observation systems, sensor data, and / or remote sensing. Experience handling large
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devote his-/or herself to his/her own education. More information about the doctoral education program at the Faculty of Medicine can be found at www.umu.se/en/faculty-of-medicine/education/doctoral
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is also required. Merits are: A particular interest in, and prior coursework in, inorganic chemistry or physical chemistry at an advanced level (at least 15 ECTS credits). Practical experience
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oral and written proficiency in English is also required. Merits are: A particular interest in, and prior coursework in, inorganic chemistry or physical chemistry at an advanced level (at least 15 ECTS
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(see below) are also encouraged to apply. Proficient in at least one programming language, preferably Python or R. Experience in any of the following areas: large scale sequence analysis, microbial