Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
than September 2025. Application Applications must be submitted electronically using the e-recruitment system of Umeå University. A complete application should contain the following documents: A cover
-
degree (at least 240 higher education credits) in Energy Engineering, Computer Science, Robotics, or Electrical and Computer Engineering. A four-year natural science degree with technical content
-
form. Please note: The applicant is responsible for ensuring that the application is complete. Incomplete applications and applications sent by email will not be considered. Application deadline: 9th
-
for ensuring that the application is complete. Incomplete applications and applications sent by email will not be considered. Application deadline: 12 May, 2025 For questions, please contact: Angela Sasic
-
application electronically via Varbi in Word or PDF format. The application deadline is XX. Additional Information Salary placement is according to the established doctoral student salary scale. Appointment
-
application form. Please note: - All application material must be submitted through Chalmers web pages, applications sent by email will not be considered. - Incomplete applications and applications sent by
-
the competence and suitability for the position Documents should be sent electronically, in MS Word or PDF format, through the recruitment system Varbi. The procedure for recruitment for the position is in
-
information about the program can be found at Doctoral studies at the Faculty of Medicine . Background and description of tasks The PhD student will use state-of-the-art methods such as cryo-electron tomography
-
academic potential Contact information (name, phone numbers and email) of two additional references Assessment Candidates will be assessed based on the following criteria: formal qualification requirements
-
will combine state-of-the-art computer vision, modeling and archived specimens to determine biotic and abiotic factors driving spatial variation in molt phenology. It will use museum genomics to recover