71 big-data-and-machine-learning-phd Postdoctoral research jobs at Technical University of Denmark
Sort by
Refine Your Search
-
is looking for a post doc with a background in seafood science and/or seafood development or processing for a large project in collaboration with Food and Agriculture Organisation (FAO), which is an
-
circular plastics economy. Learn more about the project at https://inano.au.dk/about/research-centers-and-projects/enzync . Note that the current position is based at DTU, Lyngby. Further information may be
-
digital co-simulation platforms (e.g., Modelica-Python/Simulink) Applying machine learning and data-driven approaches to enhance the operation of district heating substations Participating in course
-
, supervisor, and scientific community, promoting the lab's reputation, write reports for sponsors, research grants, and submit publications to journals Teach, supervise, and mentor undergraduate, PhD, and
-
Academic Diplomas (MSc/PhD – in English) List of publications Names and contact information of references Applications received after the deadline will not be considered. All interested candidates
-
landmark database on university deep tech startups, carry out independent, high-quality research leveraging this data, and engage with stakeholders in the Danish and international deep tech arena
-
opportunity to be part of large-scale experiments tackling pressing societal challenges. You'll be involved in every stage of the research process—from experimental design to data analysis and publication—while
-
qualification, you must hold a PhD degree (or equivalent). Further information Further information may be obtained from Professor Mayank Jain, maja@dtu.dk , +45 4677 4909. Application procedure To apply, please
-
work, including through writing peer-reviewed scientific article(s) The ideal candidate: Holds a PhD in a relevant field such as epidemiology, public health, biology, or a related discipline. Has proven
-
] that process information in temporal rather than spatial modes to reduce their footprint. The project involves a collaboration between DTU Electro (Senior Researcher Mikkel Heuck) and Harvard University (Dr