Sort by
Refine Your Search
-
, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
-
II is looking for a part-time (30 hours per week) PhD-Position: Machine Learning / Medical Imaging (m/f/x) (with immediate effect). This position is offered for a duration of 3 years. Join the AICARD
-
The Centre for Machine Learning located under the Data Science and Statistics Section of the Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark invites
-
EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
properties (hardness, yield and tensile strength) and corrosion profile (rate and localization). This work focuses on machine learning-assisted PSPR optimization of recently developed lean Mg-0.1 Ca alloy
-
machine learning approaches to quantitatively analyze experimental data and predict emergent multicellular behaviors under varying mechanical and chemical environments. For more information about our lab
-
paraganglioma driven by cell plasticity using spatial transcriptomics and machine learning.” High-risk neuroblastoma (NB) and malignant paraganglioma (PPGL) are neural crest–derived tumors with pronounced
-
, integrative biology approach that utilizes human pluripotent stem cell based model systems, high throughput functional genomic screening and big data based machine learning, bridging the scales from genetics
-
analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within
-
increasingly complex networks. By deploying and advancing techniques such as machine learning, graph-based network analysis, and synthetic data generation, the project tackles key challenges in anomaly detection
-
principles that regulate host-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine learning tools. A specific focus will be put