Sort by
Refine Your Search
-
Program
-
Employer
-
Field
-
31st July 2024 Languages English English English The Department of Engineering Cybernetics has a vacancy for a PhD Candidate PhD Candidate in Hybrid Machine Learning Apply for this job See
-
for feature extraction, which can serve as parameters in simulation. Alternatively, machine learning methods can be employed for comparison with the primary analysis-based approach. The objectives of this PhD
-
optimisation of aluminium extruded crash management systems (CMS). This research project combines operations research methodologies with machine learning techniques to revolutionise the design process, ensuring
-
on the circular design optimisation of aluminium extruded crash management systems (CMS). This research project combines operations research methodologies with machine learning techniques to revolutionise
-
solutions. The research will navigate the complexities of adversarial machine learning attacks and defenses, formulate robustness metrics, and emphasise the challenges of large language models (LLMs
-
solutions. The research will navigate the complexities of adversarial machine learning attacks and defenses, formulate robustness metrics, and emphasise the challenges of large language models (LLMs
-
: knowledge and experience within marine technology, in particular, offshore wind turbine technology knowledge and experience within machine learning motivation and potential for research within the field
-
of various sensors in care for older adults and how comprehensive data can be analyzed safely with knowledge-based machine learning. Moreover, the candidate will shed light on the questions of how data can
-
work with the ethical and financial issues surrounding the use of various sensors in care for older adults and how comprehensive data can be analyzed safely with knowledge-based machine learning
-
cand.med.vet. degree, with a learning outcome corresponding to the descriptions in the Norwegian Qualification Framework, second cycle. The applicant must have a documented strong academic background from