Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
student with a background in biological engineering, biotechnology or similar. You will work under the supervision of Assistant Professor Raphael Ferreira on large-scale genome engineering in human T cells
-
prior experience in at least three of the following areas: Python programming Develop LLM-based tools to automate data connector generation for data ingestion. Design and implement a multi-layered storage
-
of grading scale Contact details for 1–2 academic references You may apply prior to obtaining your master's degree but cannot begin before having received it. Applications received after the deadline will not
-
working with “DTU Smart Road,” a full-scale pavement research platform at DTU’s main campus that hosts embedded strain and temperature sensors. Experiments will also involve the development and installation
-
include: A letter motivating the application (cover letter) Curriculum vitae Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale You may apply prior
-
English and interpersonal skills for working in a multi-disciplinary team environment. Willingness to engage in group work with a multi-national team; Able to work independently; Approval and Enrolment
-
English in one PDF file. The file must include: A motivation letter (max 1 page) Curriculum vitae Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale FELASA
-
of grading scale. You may apply prior to obtaining your Master's degree but cannot begin before having received it. Applications received after the deadline will not be considered. All interested candidates
-
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 having received it. Applications
-
and exact optimization methods enhanced by machine learning (ML). The overarching goal is to solve large-scale combinatorial optimization problems more efficiently, particularly in domains such as