Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Czech Technical University in Prague
- Faculty of Science, Charles University
- IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava
- Institute of Computer Science CAS
- Institute of Molecular Genetics of the Czech Academy of Sciences
- MASARYK UNIVERSITY
- CEITEC MU
- Mendel University
- Česká zemědělská univezita v Praze
-
Field
-
to climate change and variability Hydrological processes in organosols and peat-affected soils Modeling Hydrological Extremes Using Machine Learning Spatial and time distribution of precipitation within
-
antibodies and anti-CD20 CAR T-cells form the backbone of treatment for mature B cell malignancies. The project focuses on elucidating changes in gene expression within the tumor microenvironment of chronic
-
Machine Learning. Profile of the graduate The graduate displays deep theoretical knowledge in molecular and cell biology, genetics and virology, with focus on some specific branch of these scientific fields
-
, dimensionality reduction and/or machine learning methods (e.g., Lasso, ridge regression) is highly desirable. Familiarity with neurostimulation, Parkinson’s disease, or neuropsychological assessment tools is
-
of dissertation topics: Developing Remote Sensing–Based Indicators of Landscape State and Change Using Data-Efficient Machine Learning Across Scales Profile of the graduate The graduates have deep theoretical
-
that preserves object identity or style. They should have a solid publication record in top-tier computer vision conferences such as CVPR, ICCV, or ECCV, and demonstrate proficiency in deep learning frameworks
-
will be integrated with statistical and machine-learning methods to classify polarity states and identify quantitative signatures predictive of metastatic behavior. The project will deliver transferable
-
animals and humans, contacts with the environment are not avoided and sometimes even actively sought. We will deploy this inspiration from biology to design truly robust machines with distributed control
-
description The project will use bioinformatic analysis together with comparative approaches to individual cells, and machine learning to investigate how the vertebrate head evolved and what mechanisms control
-
: an insight from Genetics, Single-Cell Transcriptomics, and Machine Learning. Profile of the graduate Ph.D. graduate has extensive knowledge of cell and developmental biology, ranging from basic principles