Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
Job Description Are you passionate about scientific machine learning, particularly physics-informed machine learning? If so, this position might be perfect for you. We are seeking a data scientist
-
Energy Systems (RES) section at DTU Wind and Energy Systems is inviting candidates to apply for a PhD in Modelling of power system balancing for future sector-coupled European energy systems. You will get
-
hold presentations at conferences Prepare technical reports, presentations, as well as project deliverables ensuring high standards of accuracy and presentation. Qualifications We are looking for a
-
. The fellowship is available from September 1st 2025 or as soon as possible thereafter. The PhD fellowship has a duration of three years. Job description The PhD position is part of the project “Disabling Exclusion
-
collaborative settings and wish to play a key role in an EU-funded project with researchers from multiple countries? If so, this PhD position could be a good opportunity for you. This project focuses
-
diploma (in English) including official description of grading scale You may apply prior to obtaining your master's degree but cannot begin before having received it. Applications received after
-
letter) Curriculum vitae Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale You may apply prior to obtaining your master's degree but cannot begin before
-
Job Description DTU, Department of Civil and Mechanical Engineering, the Section for Manufacturing Engineering invites applications for a PhD position (3 years) on the topic of simulation of process
-
Job Description The Department of Civil and Mechanical Engineering of the Technical University of Denmark (DTU) has an open PhD position on the topic of “Automated machine polishing of complex mould
-
with colleagues at DTU and IIT Bombay, as well as with academic and industrial partners globally. The main purpose of this PhD position is to develop, implement and assess machine learning models