Sort by
Refine Your Search
-
been directly mapped. This PhD position at Stockholm University focuses on leveraging machine learning (ML) to identify errors in large bathymetric datasets and applying ML techniques like "super
-
, Ecotoxicology, Marine Biology, Plant Physiology, Plant Systematics and Environmental and Climate Sciences. Presently around 100 people in 25 research groups work at DEEP, including 35 PhD students and 10 postdocs
-
, Ecotoxicology, Marine Biology, Plant Physiology, Plant Systematics and Environmental and Climate Sciences. Presently around 100 people in 25 research groups work at DEEP, including 35 PhD students and 10 postdocs
-
intrusion of both Atlantic and Pacific-origin waters and biota from boreal latitudes (50-70°N) into the central Arctic Ocean. The purpose of this PhD project is to gain improved understanding of pelagic
-
approaches (QM/MM, molecular dynamics, free energy methods, machine learning). The PhD candidate will work closely with other PhD students, postdocs and senior scientists of the lab in an interdisciplinary
-
approaches (QM/MM, molecular dynamics, free energy methods, machine learning). The PhD candidate will work closely with other PhD students, postdocs and senior scientists of the lab in an interdisciplinary
-
at the Department of biochemistry and biophysics, at Stockholm university. Project description Your studies in Bioinformatics will be in the project: "Deep Learning for protein structure prediction”. Protein
-
the Arrhenius Laboratories for Natural Sciences, which are situated in the northern part of the University Campus at Frescati. Some 300 people of which about 70 are PhD students work at the Department, engaged in
-
. We are seeking PhD candidates with strong and documented backgrounds in biophysics, biochemistry, molecular biology, or related fields. Proficiency with molecular cloning, protein purification, cell
-
professional research environment characterized by its well-established international profile. The institute has 30 research groups with a research staff of 180, of which 65 are PhD students. Read more about MBW