24 parallel-processing-bioinformatics Fellowship positions at UiT The Arctic University of Norway
Sort by
Refine Your Search
-
Master’s thesis, and any other academic works (published or unpublished) which the applicant wishes to be taken into consideration during the assessment process Diploma for bachelor's and master's degree
-
(EVs) and microbacteria. Current methods to characterize these particles are too slow and bulky. We want to make an on-chip system to speed up the process and make it available to do research
-
that the total time used for research training amounts to three years. We process personal data given in an application or CV in accordance with the Personal Data Act (Offentleglova). According
-
in Bremerhaven (Germany). i2B is funded for 6 years (starting in November 2024) and aims to fill a major research gap in Arctic science by investigating processes, consequences, and impact of past
-
, Natural Language Processing, and structured knowledge representations. As a researcher within Integreat, you will contribute to developing next-generation Machine Learning for advanced data analysis
-
, Natural Language Processing, and structured knowledge representations. As a researcher within Integreat, you will contribute to developing next-generation Machine Learning for advanced data analysis
-
new knowledge about the deglaciation after MIS 4 and the subsequent glacioisostatic rebound. Several sites have been identified on Svalbard, but their age, depositional processes, and indication
-
of AMR enzymes in this process. The research will be tailored to the candidate’s expertise and interests, with emphasis on interdisciplinary collaboration and openness to learning new methodologies
-
. Academic freedom and scientific and ethical principles form the basis for all UiT’s activities. Participation, co-determination, transparency and good processes will provide the decision-making basis we need
-
the group's research on developing novel machine learning/computer vision methodology. The focus of this project will be on the development of deep learning methodology for spatio-temporal medical image