Post-doctoral fellow in machine learning, imaging and big data with focus on healthcare challenges - Hiring in process/Finished, not possible to apply

Subject description

The subject, which is part of the EU Horizon consortium project TARGET, involves computational and data handling aspects for development of personalised management of stroke related to atrial fibrillation. The paradigm of digital twins penetrates the project, which aims at development of decision support tools for the stroke pathway, pathophysiology and disease onset, progression, treatment and recovery.

The position is located with the research group of Computational Science for Health and Environment.

Work duties

The main duties involved in a post-doctoral posistion is to conduct research. Teaching may also be included, but up to no more than 20% of working hours. The position shall include the opportunity for three weeks of training in higher education teaching and learning.

List of work duties:

• Research within AI and big data challenges together with some understanding of dynamical modeling.
• Collaboration with academic institutions, healthcare and industry partners within the TARGET consortium.
• Co-supervision of degree projects
• Minor teaching tasks within an introductory machine learning course.

Qualification requirements

Appointment to a post-doctoral position requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within the subject of the position, completed no more than three years before the date of employment decision. Under special circumstances, the doctoral degree can have been completed earlier.

Additional requirements:

• Very good oral and written proficiency in English.
• Good communication skills.

Assessment criteria and other qualifications

This is a career development position primarily focused on research. The position is intended as an initial step in a career, and the assessment of the applicants will primarily be based on their research qualifications and potential as researchers.

Particular emphasis will be placed on research skills within the subject.

For appointments to a post-doctoral position, the following shall form the assessment criteria:

• Good ability to develop and conduct high quality research.
• Independence.

Additional assessment criteria constituting an advantage:

• Experience of using machine learning on healthcare data.
• Experience with graph neural networks and structural casual models.
• Experience using machine learning on imaging and/or multi-modal data.

Consideration will also be given to good collaborative skills, drive and independence, and how the applicant’s experience and skills complement and strengthen ongoing research within the department, and how they stand to contribute to its future development.

Terms of employment
This is a full-time, fixed-term employment of 2 years. The period of employment is determined in accordance with the agreement “Avtal om tidsbegränsad anställning som postdoktor” (“Agreement on fixed-term employment as a post-doctoral fellow”) between Lund University, SACO-S and OFR/S, dated 1st February 2022.

Instructions on how to apply

Applications shall be written in English and be compiled into a PDF-file containing:

• résumé/CV, including a list of publications,
• a general description of past research and future research interests (no more than three pages),
• contact information of at least two references,
• copy of the doctoral degree certificate, and other certificates/grades that you wish to be considered.