Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
Python and/or Matlab. Experience with software-defined communication systems, emulation tools, and machine learning techniques is considered an advantage. Most importantly, you are eager to learn and apply
-
UiA-CERN PhD Position in Multi-robot Mapping and Environmental Data Sharing - Uncertain Environments
aims to design and implement a cloud-based architecture for storing and managing maps and associated sensor data, enabling data sharing across multiple robots and missions. It will focus on compact data
-
, and training methods - across multiple technological platforms - photonics, electronics, biological neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning
-
. More than 70 professors from multiple TUM faculties collaborate within MIRMI, fostering an exceptional environment for cutting-edge, high-impact research. Position Overview We are seeking an exceptional and
-
domains) Experience with RF signal analysis and wireless communication systems Experience with SDR platforms (e.g., USRP) and IQ data processing Experience with MATLAB and Python Excellent written and oral
-
to pack a large number of antenna elements at the transmitter and receiver side, thus enabling ultra-massive multiple-input multiple-output (UM-MIMO) with the potential of tera-bits per second data rates
-
, deposition and transport behaviour. • Wastewater treatment modelling, including aeration energy, sludge production, nutrient removal and AD performance. • MATLAB/Python-based data analysis, multi-source data
-
fusion and multirobot coordination, including multirobot perception, decentralization and mission execution. The RAI team has a strong European and National participation in multiple R&D&I projects. Duties
-
applications. Existing research model multiple UAVs as a single shared entity in a centralized Digital Twin (DT), which poses safety risks to IAM operations if the cloud or central database becomes unavailable
-
bridging digital modelling with real-world factory implementation, this project will contribute practical methodologies and guidelines for scalable, circular manufacturing systems across multiple industrial