Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
of visualisation, machine learning / AI, and human-computer interaction Very good programming skills (web-based visualisation, Python, and/or GPU programming) First experiences in the participation in research
-
biology approaches and early-adoption of cutting-edge technologies Operating with Linux and high-performance clusters (HPC) R/Python and Snakemake or Nextflow (or comparable platforms) OUR REFERENCES
-
. Electrical Engineering) strong mathematical understanding experience in programming, preferably in Python prior experience in related topics, such as machine learning, optimization, or privacy Furthermore
-
Engineering, Physics or a related technical field Good competence in Modelling and Simulation (Dymola/Modelica, gPROMS, AVEVA PS, or similar) Good competence in programming (Python) Good competence in
-
relevant experience in the field, ideally with a PhD Background knowledge in cancer genomics Proficiency in Bash scripting and R and experience with cloud computing (required) Proficiency in Python and Git
-
Doctoral Candidate in computer vision and machine learning for developing novel deep learning method
understanding of maths and physics experience in programming, preferably in Python prior experience in machine learning, computer vision and remote sensing and strong interest to apply these skills
-
fields (genetics, genomics, bioengineering, applied mathematics) Obtained or will obtain a Master’s degree in the above fields (For biologists) Intermediate programming skills in R or Python and prior
-
, and the Digital Waters Flagship initiative (https://digitalwaters.fi/ ). This role also offers opportunities to participate in funding proposals, apply for personal research funding, and engage with
-
for measuring the speed, density and viscosity are operated and further developed – some of which are unique worldwide. Area of responsibility: .... For more information, please visit our website: https
-
. Further information on data protection and the processing of personal data can be found at: https://www.isas.de/en/datenschutz . The closing date for applications is February 2, 2026. Please apply via our