Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
Skip to main content. Profile Sign Out View More Jobs Postdoc position in advancing chemical impact assessment through machine learning - DTU Sustain Kgs. Lyngby, Denmark Be the First to Apply Job
-
, relevant to the position: An internationally oriented research profile within fields such as child-computer interaction, human-computer interaction, interaction design, learning sciences or computer
-
) epidemiology, bioinformatics, statistical genetics, data science, machine learning, or a closely related discipline, and have experience with research in obesity, diabetes, cardiovascular disease, and/or life
-
Description Are you enthusiastic about basic human pain research? The Center for Neuroplasticity and Pain (CNAP) at Aalborg University is recruiting one or more postdoctoral fellows, to start 1st August 2024
-
, relevant to the position: an internationally oriented research profile within fields such as child-computer interaction, human-computer interaction, interaction design, learning sciences or computer
-
new analytical and machine learning tools that will help to interpret complex multimodal data, and you will do it in collaboration with top research scientist in the field and in an international
-
), Experience or motivation for applying statistical and machine learning methods to strain design challenges, We offer DTU is a leading technical university globally recognized for the excellence of its research
-
Research, University of Copenhagen, Denmark. Candidates should have a strong background in (genetic) epidemiology, bioinformatics, statistical genetics, data science, machine learning, or a closely related
-
Skip to main content. Profile Sign Out View More Jobs Postdoc in Computer Vision with Deep Learning for Material and Computational Design – DTU Compute Kgs. Lyngby, Denmark Job Description Do you
-
or entirely novel properties with respect to any single component (for instance, a functional entity in a biosystem). Extensions to decomposed machine-learning models developed in our lab will furthermore be