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Position: PhD student in data science focusing on federated learning applied to healthcare
Institution: Maastricht University
Location: Maastricht, Limburg, Netherlands
Duties: Maastricht University has a vacancy for a PhD student at the faculty of Health Medicine and Life Sciences in the Clinical Data Science group. At the Clinical Data Science group, we work on three main research areas: building global data sharing infrastructures; applying machine learning to build models from these data; and, using these models to improve healthcare. The PhD position is embedded in the novel Netherlands Consortium of Dementia Cohorts, a unique project to unravel the aetiology of dementia in order to find clues for primary prevention by performing pooled analyses of 9 ongoing prospective cohort studies on cognitive aging and dementia from the Netherlands. In this project, the successful candidate will be responsible for implementing federated learning infrastructure and developing federated algorithms. Federated learning has attracted the attention of major AI players like Google and Nvidia because it provides a workaround to the growing ethical and legal barriers to data sharing. Federated learning has the potential to play a key role in the next few years in the evolution of privacy-conscious, data-hungry AI, as shown by the fact that major AI conferences (e.g. Neurips, ICML) are already holding workshops dedicated to it. The successful candidate will also be in charge of data harmonization pipelines to make research data comply FAIR data principles. In addition to this project, the successful candidate will have the opportunity to apply statistical and machine learning techniques to a range of clinical problems. The successful candidate will join a cross-faculty team consisting of computer scientists, medical physicists and medical informaticians, PhD students, software engineers and post-doctoral researchers
Requirements: Specific: You have a master’s degree in data science, statistics, artificial intelligence, machine learning or equivalent and have good programming skills; Experience with machine learning, prediction modelling, ontologies, medical imaging and software engineering skills are a plus. Generic: You are an open-minded, motivated, independent, result-oriented researcher with ownership who is able to take initiative and takes pride in their work. You are fluent in English, both in speech and writing. We are looking for a researcher with a special interest in health care research and motivated to build a scientific career in the area of basic and translational research. You will closely collaborate with other members of the Clinical Data Science group
   
Text: PhD student in data science focusing on federated learning applied to healthcare at the Clinical Data Science group of the Faculty of Health, Medicine and Life Sciences - Maastricht University Published Deadline Location yesterday 1 Nov Maastricht PhD in data science focusing on federated learning applied to healthcare at the Clinical Data Science group. Job description Maastricht University has a vacancy for a PhD student at the faculty of Health Medicine and Life Sciences in the Clinical Data Science group. At the Clinical Data Science group, we work on three main research areas: building global data sharing infrastructures; applying machine learning to build models from these data; and, using these models to improve healthcare. The PhD position is embedded in the novel Netherlands Consortium of Dementia Cohorts , a unique project to unravel the aetiology of dementia in order to find clues for primary prevention by performing pooled analyses of 9 ongoing prospective cohort studies on cognitive aging and dementia from the Netherlands. In this project, the successful candidate will be responsible for implementing federated learning infrastructure and developing federated algorithms. Federated learning has attracted the attention of major AI players like Google and Nvidia because it provides a workaround to the growing ethical and legal barriers to data sharing. Federated learning has the potential to play a key role in the next few years in the evolution of privacy-conscious, data-hungry AI, as shown by the fact that major AI conferences (e.g. Neurips, ICML) are already holding workshops dedicated to it. The successful candidate will also be in charge of data harmonization pipelines to make research data comply FAIR data principles. In addition to this project, the successful candidate will have the opportunity to apply statistical and machine learning techniques to a range of clinical problems. The successful candidate will join a cross-faculty team consisting of computer scientists, medical physicists and medical informaticians, PhD students, software engineers and post-doctoral researchers. Specifications max. 38 hours per week €2395—€3061 per month Maastricht View on Google Maps Maastricht University (UM) Requirements Specific: You have a master’s degree in data science, statistics, artificial intelligence, machine learning or equivalent and have good programming skills. Experience with machine learning, prediction modelling, ontologies, medical imaging and software engineering skills are a plus. Generic: You are an open-minded, motivated, independent, result-oriented researcher with ownership who is able to take initiative and takes pride in their work. You are fluent in English, both in speech and writing. We are looking for a researcher with a special interest in health care research and motivated to build a scientific career in the area of basic and translational research. You will closely collaborate with other members of the Clinical Data Science group. Conditions of employment Fixed-term contract: 4 years. The full-time position is offered for four years (1 3), with a yearly evaluation. Your salary would be € 2.395,- gross per month in the first year up to € 3.061,- gross per month in the fourth year according to the PhD-candidate salary scale. On top of this, there is an 8% holiday and an 8.3% year-end allowance. The terms of employment of Maastricht University are set out in the Collective Labour Agreement of Dutch Universities (CAO). Furthermore, local UM provisions also apply. For more information look at the website www.maastrichtuniversity.nl > Support > UM employees. Employer Maastricht Univeristy Maastricht University is renowned for its unique, innovative, problem-based learning system, which is characterized by a small-scale and student-oriented approach. Research at UM is characterized by a multidisciplinary and thematic approach, and is concentrated in research institutes and schools. Maastricht University has around 18,000 students and 4,400 employees. Reflecting the university's strong international profile, a fair amount of both students and staff are from abroad. The university hosts 6 faculties: Faculty of Health, Medicine and Life Sciences, Faculty of Law, School of Business and Economics, Faculty of Science and Engineering, Faculty of Arts and Social Sciences, Faculty of Psychology and Neuroscience. Department GROW- School for Oncology and Developmental Biology The School for Oncology & Developmental Biology (GROW) focuses on research and teaching of genetic and cellular mechanisms, as well as environmental and life-style factors that underlie normal (embryonic and fetal) and abnormal (cancer) development. The emphasis is on basic and translational research, aiming at innovative approaches for individualizing prevention, patient diagnosis, and treatment for genetically determined diseases and cancer. https://www.maastrichtuniversity.nl/research/school-oncology-and-developmental-biology Clinical Data Science group The Clinical Data Science group is a computer science focused department embedded within a clinical environment (MAASTRO Clinic and Maastricht UMC). The Clinical Data Science group focuses on three main research areas: building global data sharing infrastructures; applying machine learning to build models from these data; and, using these models to improve healthcare. Additional information For more information you can contact: Manager Research & Education, Andre Dekker: andre.dekker@maastro.nl Postdoctoral researcher, Inigo Bermejo: Inigo.Bermejo@maastro.nl Twitter
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