Postdoc position in applied machine learning to develop risk prediction tools in atrial fibrillation
Aalborg Universitet
A Horizon Europe funded Postdoc position in machine learning is available at Center for Clinical Data Science, Department of Clinical Medicine, Aalborg University. The position is for two years. Starting date will be 1 September 2024 or soon hereafter. About Center for Clinical Data Science (CLINDA). The center is a part of Department of Clinical Medicine, Aalborg University and Research, Education, and Innovation, Aalborg University Hospital and works primarily with application and methodological development of bioinformatics, biostatistics, machine learning, and data management within clinical research. The center is highly interdisciplinary and employs biostatisticians, bioinformaticians, software developers, biomedical engineers, and data managers who collaborate closely with healthcare professionals throughout the Danish healthcare sector. Based on health care data and molecular biomarkers, the focus is currently on establishing scalable, national decision support tools for personalized medicine.JobbeskrivelseAbout the positionYou will join the ambitious European collaboration ARISTOTELES(Applying artificial intelligence to define clinical trajectories for personalized prediction and early detection of comorbidity and multimorbidity patterns). Further, you will contribute to ARISTOTELES’ aim to leverage artificial intelligence for the personalized prediction and early detection of comorbidity and multimorbidity patterns in atrial fibrillation patients. The key responsibility of the position is to structure atrial fibrillation patient’s health data for machine learning algorithms(feature engineering), contribute to the development of machine learning based algorithms for predicting complications to atrial fibrillation, and implementation of predictive models in the clinic.You will work with key stakeholders across Europe and at Aalborg University you will work closely with researchers at Danish Center for Health Services Research and Center for Clinical Data Science, Department of Clinical Medicine and Data, Knowledge, and Web Engineering at Department of Computer Science, Aalborg. This is a unique opportunity to work in a multi-disciplinary, collaborative environment at the interface of computational healthcare and machine learning.For further information:
Please contact, Head of Center, Professor Martin Bøgsted, , tel.+45 5092 5639 or Group Leader, Assistant Professor, Charles Vesteghem, , tel.+45 6166 7681.QualificationsYou should hold a PhD degree in computer science, statistics, physics, mathematics, engineering, or a field of science relating to data science. You are expected to have:
It will be a plus, if the candidate has experience with one or more of these additional criteria:
Valued personal competencies are:
The applicationThe application must contain the following:
Application processThe applications are only to be submitted online by using the”Apply online” button below.Shortlisting will be applied. After the review of any objections regarding the assessment committee, the head of department, with assistance from the chair of the assessment committee, selects the candidates to be assessed. All applicants will be informed as to whether they will advance to assessment or not.AAU wishes to reflect the diversity of society and welcomes applications from all qualified candidates regardless of personal background or belief.For further information concerning the application procedure please contact HR Partner Jeannette Bøgh by mail . Information regarding guidelines, ministerial circular in force and procedures can be seenLøn og ansættelsesvilkårEmployment is in accordance with the Ministerial Order on the Appointment of Academic Staff at Universities(the Appointment Order) and the Ministry of Finance’s current Job Structure for Academic Staff at Universities. Employment and salary are in accordance with the collective agreement for state-employed academics.
Aalborg, Nordjylland
Sat, 08 Jun 2024 23:59:36 GMT
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