39 machine-learning-and-image-processing-"RMIT-University" PhD research jobs in Germany
Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
models. Your tasks: Research, development, and evaluation of Machine Learning and Deep Learning methods Prototype development Literature review Publication and presentation of scientific results in
-
the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
-
Chair of Biological Imaging 07.08.2025, Wissenschaftliches Personal We are now looking for a highly qualified and motivated researcher with an engineering or physics background (f/m/x) and a
-
for imaging plant tissues (rose cuttings) Realisation of a corresponding measuring stand and implementation of test series for imaging Realisation of a data processing routine for the automated detection
-
corpora data correlation. Requirements: A master’s degree in Computational Linguistics, Computer Science or related fields. Solid background in Machine Learning and Natural Language Processing Experience
-
disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with
-
measuring stand for the collection of hyperspectral data on a test field Collection of imaging data and creation of a database Establishment of a data processing routine for pre-processing the hyperspectral
-
a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation
-
/intercultural communication Experience in processing imaging data is a plus Experience with the named imaging modalities or other optical technologies for plant phenotyping is a plus Equal opportunities and
-
Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta