Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
will be part of the Institute for Lifespan Development, Family and Culture: https://www.uni.lu/fhse-en/research-groups/institute-for-lifespan-development-family-and-culture/ Responsibilities: Obtaining a
-
the Australian Research Council, will focus on the development and testing of (U-Th)/He dating techniques applied to “non-traditional” accessory minerals in order to develop novel tools for Quaternary magmatic
-
PhD Scholarship in Big Data and Analytics for Crop Genetics Modern agriculture and biomedical research are driven by the availability of big data and the development of data science. The recent
-
, cutting-edge microscopy, immunology, technology development, and bioinformatics. VIB provides a highly interactive environment and ample training opportunities for its researchers. The VIB-UAntwerp Center
-
from established collaborations and access to centralized facilities with expertise in functional genomics and cell biology, proteomics, cutting-edge microscopy, immunology, technology development, and
-
the development of the rule of law in the Global South. Being part of the project will allow the doctoral researcher to enhance his/her knowledge-base and experience; working on the various aspects
-
and spectroscopy Construction and optimization of single-molecule microscopy setups Development of image- and signal-processing software for single-molecule microscopy and spectroscopy data Analysis
-
the genetic etiology and developing diagnostics and treatment methods for these diseases. Approaches range from human genetics, genomics, protein biochemistry and neuronal and glial cell biology to integrative
-
the genetic etiology and developing diagnostics and treatment methods for these diseases. Approaches range from human genetics, genomics, protein biochemistry and neuronal and glial cell biology to integrative
-
. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop machine learning surrogates of wind energy systems. As newer