43 Environment scholarships at UiT The Arctic University of Norway

PhD Fellow in Tumor Biology

environment As many people as possible should have the opportunity to undertake organized research training. If you already hold a PhD or have equivalent competence, we will not appoint you to this position

PhD Fellow in Tumor Biology

are looking for candidates who: Have good collaboration skills Have good communication and interaction with colleagues and students Wants to contribute to a good working environment As many people as possible

PhD fellow in Computer Science

fluency of in English and be able to work in an international environment. Nordic applicants can document their English capabilities by attaching their high school diploma.  Working knowledge of Norwegian

PhD Fellow in Optics – Optical Tomography

employees and students, and to create an inclusive and safe working environment. We believe that inclusion and diversity are a strength, and we want employees with different competencies, professional

PhD Fellow in knowledge-driven machine learning

fluency of in English and be able to work in an international environment. Nordic applicants can document their English capabilities by attaching their high school diploma. Working knowledge of Norwegian

PhD Fellow in Optics – Optical Tomography

employees and students, and to create an inclusive and safe working environment. We believe that inclusion and diversity are a strength, and we want employees with different competencies, professional

PhD fellow in Computer Science

international environment. Nordic applicants can document their English capabilities by attaching their high school diploma.  Working knowledge of Norwegian or a Scandinavian language is also beneficial

PhD Fellow in knowledge-driven machine learning

able to work in an international environment. Nordic applicants can document their English capabilities by attaching their high school diploma. Working knowledge of Norwegian or a Scandinavian language

PhD Fellow in Deep Learning and statistics for heterogeneous data

descriptions, location, and various seabed geophysical measures. This allows for a more comprehensive and accurate understanding of marine environments and ecosystems. This project will develop novel directions

PhD Fellow in Deep Learning and statistics for heterogeneous data

environments and ecosystems. This project will develop novel directions within multimodal deep learning which utilizes heterogeneous data to improve deep learning models for environmental monitoring