153 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Sweden
Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Lund
- Chalmers University of Technology
- Nature Careers
- Swedish University of Agricultural Sciences
- SciLifeLab
- Umeå University
- Linköping University
- Lulea University of Technology
- Linnaeus University
- Mälardalen University
- Örebro University
- Jönköping University
- Blekinge Institute of Technology
- European Magnetism Association EMA
- Karlstad University
- 5 more »
- « less
-
Field
-
in computer science, mathematics, statistics, bioinformatics, or equivalent. The candidate should have previous experience in bacterial genomics, machine learning/artificial intelligence, preferably
-
systems, and machine learning. While the initial focus of the position is on this project, we offer significant opportunity for the applicant to develop their own independent research trajectory in
-
Injection Systems (CIS) — natural protein machines used by bacteria to deliver molecular cargo. The group's mission is to understand the structure, function, and application of CIS for use in both
-
of PhD and MSc students, teaching and supporting in acquiring funds for future research projects from research funding agencies/councils, EU framework program or industry. Qualifications Eligibility
-
. The applicant should be proficient in written and spoken English, and have good computer skills (e.g Word, Photoshop, BioRender, Excel). Also, it is important that the candidate demonstrates independence, as
-
Institute of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work may include clinical and biomedical projects. It may
-
collaborate with multiple stakeholders and conduct applied research in silviculture, forest ecology, pathology, policy and planning. We teach bachelor, Masters and PhD level courses addressing all
-
sequencing and synthesis to design useful cell behaviors. The scope of this project is to combine multi-gene control technology and computer algorithms to develop a foundational discovery platform for future
-
fluids, flow-induced pattern formation in both simple and complex flows (e.g. flow instabilities, product defects), multiscale analysis, and the application of machine learning techniques. About the
-
, you must hold a PhD (awarded no more than three years prior to the application deadline*) in computer science, maritime transportation, or a related field, with a strong foundation in mathematics and