Sort by
Refine Your Search
-
Financing yes Type of Position Full PhD Working Language English Required Degree Master Magister (Masters degree course) Areas of study Marketing, Distribution, Commercial Law, Economic Sciences, Economics
-
highly collaborative and interdisciplinary research environment, where you'll work alongside experts from fields such as transport and urban planning, engineering, data science, computer science. Skill
-
- looking. Sensor technology plays a key role in this transformation, enabling real-time monitoring, automation, and intelligent decision-making. Despite these needs, many water treatment processes still rely
-
University, Faculty of Chemistry - more information about the PhD program at the HZDR can be found here Salary and social benefits in accordance with the collective agreement for the public sector (TVöD-Bund
-
“PhytoM - Leibniz Professorship for Phytonutrient Management” at the Technische Universität Berlin: PhD student (f,m,div) in the Field of Physiology and Food Chemistry Reference number: 21/2025/3 The salary
-
and urban planning, engineering, data science, computer science. Skill Development: Our extensive qualification concept goes beyond research, offering targeted training in research methods, project
-
or very good university degree (diploma, master's degree) in transport or related study programs (e.g., civil engineering, industrial engineering, computer science, etc) with a solid foundation in transport
-
Description The Institute of Energy Technologies – Fundamental Electrochemistry (IET-1) focuses on the development of performance-oriented and sustainable materials and components for the electrochemical energy storage and conversion. Aiming to develop sustainable and cost-effective batteries,...
-
. The successful candidate will receive careful mentorship both from the supervisor and from other peers through a dedicated mentorship program. Technical queries should be directed to Benedikt Jahnel
-
computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and