Sort by
Refine Your Search
-
their results on advanced equipment. For further information, you may check: wwwen.uni.lu/snt/research/spacer and www.spacer.lu The candidate will lead the development of a V&V framework for AI-augmented
-
Postdoctoral position in Bioinformatics/Computational Biology (m/f/d) (full-time position 100 % ~ 38
package development) and command line-based analysis tools (e.g. Python) • Knowledge with public sequence databases, error correction algorithms • Scientific experience in immunology, molecular and cell
-
. PyTorch). Experience analyzing high-dimensional data (biological or otherwise) or single-cell, bulk sequencing, or other biological data. Experience in algorithms and good software development practices
-
control technology and computer algorithms to develop a foundational discovery platform for future cell programming applications. This position involves both experimental and computational work
-
on the creation and application of predictive simulation models Collaboration on the development of data processing and fusion algorithms Collaboration on the virtual modeling of marine structures Conducting and
-
division 8.5 Planning, performing, and evaluating in-situ/4D computed tomography experiments Developing software for the quantitative evaluation of various image data sets (algorithms for detecting volume
-
computational approaches to uncover novel biomarkers and therapeutic strategies for CNS disorders. Key Responsibilities: Develop and implement algorithms for multimodal image fusion, combining data from MRI, PET
-
opportunity to contribute to cutting-edge research at the intersection of artificial intelligence, machine learning, and healthcare. The successful candidate will develop and apply advanced machine learning
-
As a fellow you will join our faculty in the Department of Biostatistics, providing statistical support and developing innovative biostatistical methods for research projects at the cutting edge
-
disease into specific subclasses. You will develop AI algorithms to train models that predict if individuals (from which we create circuits) are prone to develop disease and to identify conditions that have