Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
responsibilities As a postdoctoral researcher in the group, you will need to perform sample preparation, data collection and analysis work as agreed during regular meetings. You will also need to participate in
-
-der-valk/ ). We are looking for someone with a passionate interest in insect phylogeny and evolution, and with strong competence in de novo genome assembly and phylogenomic analysis. The successful
-
://ngisweden.scilifelab.se/ ). Description of work You will contribute to the development and implementation of novel methods and technologies for genome, transcriptome and epigenome analysis, both in bulk and at single-cell
-
to work on topics at the intersection of applied probability and analysis. The group around Pierre Nyquist currently consists of three PhD students and is focused on questions in probability theory and
-
). This position offers a unique opportunity to collaborate closely with researchers across the Division of Marine Technology at Chalmers University, with a focus on maritime transportation risk analysis. Project
-
analysis, work with large language models, network analysis, causal inference in machine learning and agent-based modelling. Experience in collecting, curating and analyzing large digital datasets with
-
data acquisition) and profound skills in XANES & EXAFS data analysis Strong track record of publications in X-ray spectroscopy and a strong drive towards research publications Proficiency in English
-
techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get unprecedented medical
-
experiments, molecular cloning, cell culture, and standard laboratory methods such as flow cytometry and RT-qPCR. The computational work includes, for example, the analysis of omics data and computational
-
fluids, flow-induced pattern formation in both simple and complex flows (e.g. flow instabilities, product defects), multiscale analysis, and the application of machine learning techniques. About the