184 parallel-and-distributed-computing-"Multiple" positions at Technical University of Denmark in Denmark
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
an international, interdisciplinary research environment. At DTU, you will be part of the PCAS, and you will find yourself among multiple PhD students and senior researchers working on multiple aspects
-
Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA Reference Number DC5 Marie Curie Grant Agreement Number 101225914 Is the Job related to staff position within a
-
commercialized by a DTU spin-out (Spectroinlets) - but we have to move beyond what we already have in order to enable automated detection of non-volatile products. This will be your main objective. In parallel
-
meet security, compliance, and integration requirements. You will collaborate with various professionals and act as the link between technical teams, clinical teams, and project management. In parallel
-
consumers. You'll gain deep interdisciplinary experience—combining multiple data layers and approaches including bioinformatics, machine learning, food safety management, regulatory science, genomics and user
-
multiple systems Driving use-case studies that demonstrate the benefits of semantic integration, e.g. in scheduling, resource sharing, or formulation optimization Collaborating with chemical engineers
-
Job Description Do you have a background in bioinformatics or AI/ML? Do you wish to do a PhD whereby you use your computational skills to discover new insights in industrially important bacteria
-
relation to having the optimal phase development during hardening, as the volume distribution of the phases and the molecular structure are not entirely optimal. Since we want to contribute to a circular
-
undermine this future. Can you see how Machine Learning, Computer Vision, and Robotics can open up opportunities for autonomously operating agricultural robots? Are you passionate about making agriculture
-
graph using RDF, OWL, and related technologies Designing and implementing workflows for data ingestion, integration, and querying across multiple systems Driving use-case studies that demonstrate