Post-doctoral Fellow in Machine Learning: Lund University, renowned globally since its founding in 1666, invites applications for a full-time, fixed-term position as a Post-doctoral Fellow in the field of Computational Science for Health & Environment. The position is part of the EU Horizon consortium project TARGET, focusing on personalized stroke management related to atrial fibrillation through the development of decision support tools.
Post-doctoral Fellow in Machine Learning, Imaging, and Big Data for Healthcare Challenges
Designation: Post-doctoral Fellow
Research Area: Computational Science for Health & Environment
Location: Lund, Skåne län, Sweden
Eligibility/Qualification: Applicants must have a Ph.D., or an international equivalent, completed no more than three years before the employment decision. Strong proficiency in English and good communication skills are essential. The candidate should have expertise in AI, big data challenges, and dynamical modeling, with additional qualifications in machine learning on healthcare data considered advantageous.
Job Description: The post-doctoral fellow will conduct research in AI and big data challenges, emphasizing dynamical modeling. Collaborative efforts with academic institutions, healthcare, and industry partners within the TARGET consortium are integral. Responsibilities include co-supervision of degree projects, minor teaching tasks in an introductory machine learning course, and contributing to the ongoing research in the department. The position provides an opportunity for three weeks of training in higher education teaching and learning.
How to Apply: Interested candidates should submit their applications in English as a PDF file, including a résumé/CV, a list of publications, a description of past and future research interests (up to three pages), contact information for at least two references, and copies of relevant certificates/grades. Applications should be sent to vacancies@harper-adams.ac.uk by no later than midnight on 08 March 2024.
Last Date for Apply: 08 March 2024 11:59 PM CET
Table: Key Information
Attribute | Information |
---|---|
Type | Temporary position |
Contract Type | Full time |
First Day of Employment | Negotiable/ According to the agreement |
Salary | Monthly |
Number of Positions | 1 |
Full-time Equivalent | 100 |
City | Lund |
County | Skåne län |
Country | Sweden |
Reference Number | PA2024/385 |
Contact | Mattias Ohlsson, mattias.ohlsson@cec.lu.se |
Union Representative | OFR/ST:Fackförbundet ST:s kansli, 046-2229362 |
Published | 09 Feb 2024 |
Last Application Date | 08 Mar 2024 11:59 PM CET |