70 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" Fellowship research jobs in Norway
Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
intelligence/machine learning skills. The candidate’s research proposal must be closely connected to the call and the research of NCEI. Excellent skills in written and oral English. Personal suitability and
-
groundwater/geochemical modelling software (e.g., MODFLOW, PHREEQC). Experience with laboratory analytical methods (e.g., chromatography, mass spectrometry). Familiarity with AI or machine learning applications
-
Science About the project This PhD project integrates pharmacoepidemiology, causal inference, and machine learning to study real-world treatment patterns, effectiveness, and safety of monoclonal antibodies
-
the areas of stochastic analysis and computational methods towards machine learning with focus on risk-sensitive decision making and control. Techniques may include forward, backward stochastic differential
-
of AI and in particular machine learning (ML). As today’s mainstream AI/ML workloads often resort to large-scale and energy-hungry supercomputers, it is necessary have a more critical look at how HPC
-
, including individually tailored career development plans with formal supervision and project-based learning. Secondments, consortium meetings, and workshops will provide hands-on experience in collaborative
-
refractive-index imaging of complex samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue
-
educational system. Strong background in molecular modeling, molecular dynamics simulations, or computer-aided drug design. Proven record of programming language through publicly available Github/Gitlab
-
dynamics simulations, or computer-aided drug design. Proven record of programming language through publicly available Github/Gitlab or similar repositories. Experience in the cell biology lab Fluent oral and
-
kind of machine learning algorithm, provides more accurate data than traditional data collection methods, e.g. paper-based surveys. This data is valuable to several stakeholders: i) architects and urban