Sort by
Refine Your Search
-
Category
-
Country
-
Employer
- Delft University of Technology (TU Delft)
- NEW YORK UNIVERSITY ABU DHABI
- Carnegie Mellon University
- Chalmers University of Technology
- Cornell University
- Eindhoven University of Technology (TU/e)
- Aarhus University
- EPFL
- Harvard University
- KTH Royal Institute of Technology
- Maastricht University (UM)
- Oak Ridge National Laboratory
- Pennsylvania State University
- Brookhaven National Laboratory
- CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences
- ETH Zürich
- FAPESP - São Paulo Research Foundation
- IOCB Prague (Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences)
- MOHAMED BIN ZAYED UNIVERSITY OF ARTIFICIAL INTELLIGENCE
- Massachusetts Institute of Technology
- Mohamed bin Zayed University of Artificial Intelligence
- Nencki Institute of Experimental Biology
- New York University
- Norwegian University of Life Sciences (NMBU)
- Princeton University
- Technical University of Munich
- The University of Arizona
- University College Cork
- University of Arkansas
- University of Lund
- University of Oxford
- University of Oxford;
- Université de Caen Normandie
- VIB
- 24 more »
- « less
-
Field
-
established and emerging bioinformatics, statistical modelling, and machine learning approaches to analyse large-scale datasets, including bulk and single-cell sequencing, gene expression arrays, proteomics
-
genomics modalities Background in immunology or inflammatory disease Experience with machine learning methods applied to large data Background in immunology, infectious disease, or inflammatory disease
-
in tropical regions; analyze links between macrofauna and soil carbon; build/validate scoring algorithms using machine learning/cumulative functions. Outputs – Lead scientific, technical, and policy
-
employees and conducts research and teaching mainly in electrical engineering and computer technology. We are located on LTH's campus in northern Lund. Within the Division of Electromagnetics and
-
of Singapore, and EPFL (Switzerland). These partners are looking for talents in several domains of machine learning, AI, computational biology, and biology, to develop PhD theses across the main pillars
-
or more of the following areas: (1) Generative AI and machine learning, (2) affective computing, (3) human-computer interaction or collaborative AI, and (4) interaction design, experimental design or
-
developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
-
modelling, and machine learning approaches to analyse large-scale datasets, including bulk and single-cell sequencing, gene expression arrays, proteomics, and metabolomics. Working closely with senior
-
modeling, machine learning, • Experience in human electrophysiological research is a plus, experience in intracranial human research large plus, • Knowledge of cognitive system is a plus, knowledge of
-
Researcher in The School of Chemistry. The InTeleCat project involves the use of machine learning and AI as applied to organic synthesis. It is a large collaborative project involving researchers in the US