Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
the carbon footprint of milk production. The project will apply advanced statistical methods, artificial intelligence, and cutting-edge genetic models to support and enhance management and breeding decision
-
skills: Experience with machine learning and statistics Knowledge on mutational mechanisms in cancer Publications as co-author or first author in a related area Fellowships, grants and prizes Place of
-
Solid experience with statistical modeling, machine learning, or AI Practical skills in R and/or Python for data analysis and model development Familiarity with microbial ecology, genomics, or food safety
-
with a wide range of data formats and engaging with data experts and database managers. The second major focus is advanced data analysis and statistical modeling to identify patterns in fish distribution
-
algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
-
, proteomics) and bioinformatic analysis. Proficiency in data analysis, statistics, and excellent communication and collaboration skills are also desired. Excellent oral and written English language skills are a
-
used will be Density Functional Theory, statistics, machine-learning and dynamics. Collaboration with members of other research groups at UCPH and abroad is required. Who are we looking for? We
-
degrees in either the natural sciences (chemistry, physics, mathematical/computational biology) or in the formal sciences (statistics, computer science, mathematics), but must have a serious interest in
-
, particularly GBS, continuous-variable QC Experience with numerical simulation, statistical estimation, or probabilistic modeling. Programming proficiency (Python, Matlab or C++), especially for numerical
-
. CLASSIQUE is organized into four research thrusts that rely upon interdisciplinary competences in: communication theory, networking, information theory, physics, mathematics, computer science, and statistics