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
-
languages. We welcome and value diversity in our working environment. Information about the PhD programme at MISU . Project description In this project, we have a vision of further developing the so called
-
diffraction, electron microscopy, electron crystallography, solid-state NMR, and computer modelling of materials with a potential for various applications. Research activities in the area of Analytical
-
. The project revolves around our new agoTRIBE method, to experimentally map miRNA targets transcriptome-wide in single cells. The PhD student will computationally analyze single-cell data and integrate it with
-
opportunities for all. Contact For more information, please contact the project leader, Professor Arne Elofsson, [email protected] . General information about the PhD programs can be given by the Director
-
. General information about the PhD programs can be given by the Director of Doctoral Studies, Pia Ädelroth, [email protected] or the Head of the Department, Martin Högbom, [email protected]
-
. These methods are very powerful, but they are complex, low in throughput and expensive. In order to scale targeted spatial omics methods to allow large studies of clinical cohorts, or for diagnostic applications
-
of the earliest stable cells. This is a highly interdisciplinary project in the crossroads of biophysics, data science and physical chemistry. As a PhD student you will be part of a team exploring biochemical
-
26 Mar 2024 Job Information Organisation/Company Stockholm University Research Field Chemistry » Structural chemistry Chemistry » Inorganic chemistry Researcher Profile First Stage Researcher (R1
-
. Animal studies of developmental neurotoxicity (DNT) are time-consuming, expensive, use a large number of animals, and have shortcomings including a limited comprehensiveness of the endpoints measured. Few