Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
to: Gas sensor selection and characterization Embedded system integration Mechanical design (CAD) and 3D printing Data collection and analysis Basic machine learning for sensor data interpretation Start
-
Computer Vision There is growing trend towards explainable AI (XAI) today. Opaque-box models with deep learning (DL) offer high accuracy but are not explainable due to which there can be problems in
-
, bioinformatics, aging biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and
-
, Denmark [map ] Subject Areas: Nonparametric estimation, Machine learning methods in econometrics and time series analysis, Statistics for high-dimensional data, Stochastic volatility models Appl Deadline
-
high-throughput reactor systems, combined with the implementation of a visionary data management strategy, will provide a unique environment for data-rich research supported by machine learning and AI
-
computer science. The candidate is expected to have solid knowledge in most of the following areas: Robotics Control theory Deep Learning & Machine learning Modelling and control of soft/continuum robots Experience
-
Bioinformatics Staff Scientist at the Center for Adipocyte Signaling (ADIPOSIGN) (Academic Employee)
for exploratory data analysis and data sharing Experience in Machine Learning would be desirable Passion for complex data visualization and representing data into interpretable figures. Ideally at least one major
-
obtainable using the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. Furthermore, the postdoc will aid in
-
obtainable using the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. This postdoc position will utilize
-
the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. The postdoc will be part of the Microbial Metagenomics group