24 coding-"https:"-"FEMTO-ST"-"Prof"-"AMOLF" "https:" "https:" "https:" "https:" "https:" "I.E" positions in Norway
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getting Bayesian type uncertainty for parameters given data (i.e., a posterior type distribution over the parameter space) without specifying a model nor a prior. Such methods can in principle be applied
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’. The position forms part of the larger ERC-funded AFRI-FOR project (https://afrifor.info/ ). In developing countries, reconciling nature protection and development goals (food security, poverty alleviation) make
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field and laboratory work Thrives in an interdisciplinary research and teaching environment Remuneration and further information The position is placed in position code 1017 PhD. Fellow, NOK 550.800
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CountryNorwayCityTrondheimPostal Code7491StreetHøgskoleringen 1Geofield Contact City Trondheim Website http://www.ntnu.no Street Høgskoleringen 1 Postal Code 7491 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More
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Website http://www.ntnu.no Street Høgskoleringen 1 Postal Code 7491 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo Gmail Weibo Blogger Qzone
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EnergyCountryNorwayCityTrondheimPostal Code7491StreetHøgskoleringen 1Geofield Contact City Trondheim Website http://www.ntnu.no Street Høgskoleringen 1 Postal Code 7491 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More
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‑quality international journals. Remuneration and further information The position is placed in position code 1017 PhD. Fellow, (NOK 550 800). Seniority promotion in the position. Admission to a PhD program
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/Province Troms City Tromsø Website https://en.uit.no/startsida Street Hansine Hansens veg 18 Postal Code 9019 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket
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applications Strong oral and written communication skills in English Knowledge of a Scandinavian language is an advantage Remuneration and further information The position is places in position code 1017 PhD
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getting Bayesian type uncertainty for parameters given data (i.e., a posterior type distribution over the parameter space) without specifying a model nor a prior. Such methods can in principle be applied