Sort by
Refine Your Search
-
Category
-
Employer
-
Field
-
humans and society at large is either fully automated or heavily relies on automatically provided decision support. While machine learning approaches become increasingly prevalent in this context
-
Technology Laboratory (QTL) division of the Microtechnology and Nanoscience (MC2) department, working in a large team of PhDs, postdocs and researchers. About the research We are seeking PhD students to work
-
using state-of-the-art single-cell omics technologies. The team consists of the principal investigator, two experimental scientists (doctoral students), one bioinformatician (postdoc), and one
-
engineering challenges. Currently, three postdocs and about 15 PhD students are working within our main research areas: Lightweight materials and structures, multi-phase and metallic materials, Process modeling
-
will be expanded with the recruitment of 19 academic and 7 industrial PhD students. During the course of the DDLS program more than 260 PhD students and 200 postdocs will be part of the Research School
-
postdocs at Chalmers, and collaborate with academic and industrial partners in Sweden and internationally. The role also offers opportunities for travel and engagement with external collaborators. Research
-
, Internet of Things, Systems-of-Systems automation, Machine Learning, Deep Learning, Data Science, Electronic systems design, and sensor systems. Cyber-Physical Systems (CPS) focuses on integrated software
-
of the DDLS program more than 260 PhD students and 200 postdocs will be part of the Research School. The DDLS program has four strategic research areas: cell and molecular biology, evolution and
-
, Internet of Things, Systems-of-Systems automation, Machine Learning, Deep Learning, Data Science, Electronic systems design, and sensor systems. Cyber-Physical Systems (CPS) focuses on integrated software
-
of novel computational methods and models, including extending methods already under development in the lab, with a particular focus on ways of exerting more precise control for protein design. In