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Position: Postdoc in Bias and Fairness for Medicine
Institution: Technical University of Denmark
Location: Kongens Lyngby, Lyngby‐Taarbæk Municipality, Denmark
Duties: The goal of the project is to collaborate with researchers in ethics for AI to formulate new concepts of fairness specialized for medicine; derive mathematical models for how predictive algorithms will be fair in this new sense; and to document the effect of dataset bias on fair versus un-corrected algorithms via a registry study of diagnostic bias in depression
Requirements: You should have a PhD degree in computer science, statistics, mathematics or a similar degree; An unstoppable drive and excitement for developing responsible machine learning algorithms; A documented solid background in either machine learning or statistics; Programming experience, in particular including Python
   
Text: Postdoc in Bias and Fairness for Medicine DTU Compute Share on Facebook Share on Twitter Share on Linkedin Tuesday 06 Apr 21 Apply for this job Apply no later than 1 May 2021 Apply for the job at DTU Compute by completing the following form. Apply online As a postdoc in bias and fairness for medicine, you will be part of the section for Visual Computing at DTU Compute. We are a lively research environment dedicated to machine learning, statistics and algorithms to solve methodological and applied problems within imaging, computer graphics and related fields. You will also be affiliated with the Neurobiology Research Unit (NRU) at Rigshospitalet (www.nru.dk), a cross-disciplinary research center focusing on brain neurobiology and advanced data analytic approaches of neuroimaging data. You will be part of the research project "Bias and Fairness in Medicine", which aims to develop new concepts of fairness for medicine in a collaboration that involves both machine learning, medicine, and ethics. While state-of-the-art fair algorithms largely focus on mathematically constraining predictive algorithms to be fair in a legal sense, these constraints typically lead to decreased predictive power, which may be problematic in medicine: Are we willing to reduce our ability to diagnose depression in females just because we are less able to diagnose it in males? In collaboration with ethics, you will formulate new concepts of fairness and derive mathematical models for medical AI algorithms that increase fairness. Responsibilities and qualifications The goal of the project is to collaborate with researchers in ethics for AI to formulate new concepts of fairness specialized for medicine; derive mathematical models for how predictive algorithms will be fair in this new sense; and to document the effect of dataset bias on fair versus un-corrected algorithms via a registry study of diagnostic bias in depression. In particular: You will contribute to a registry study on depression, documenting bias in diagnosis on the dataset, and documenting how the dataset bias propagates to predictive algorithms trained on the dataset. You will develop mathematical models of fairness within medicine in collaboration with researchers within ethics for AI Your research could include popular scientific dissemination to the general public and popular media. This is an interdisciplinary research project involving three research groups: The group of Aasa Feragen (DTU Compute) which specializes in machine learning for biomedical imaging and related problems; the group of Melanie Ganz (NRU) which specializes in statistical methods for neuroimaging, and the group of Sune Hannibal Holm (University of Copenhagen), which specializes in ethics for AI. While your base will be at DTU Compute, you will be co-affiliated with NRU, where the registry study will be located. You will also collaborate actively with the ethics group, in particular for deriving new, ethically motivated, concepts of fairness. You will also be part of the Center for Basic Machine Learning Research in Machine Learning . You should have a PhD degree in computer science, statistics, mathematics or a similar degree. Additionally, you should have An unstoppable drive and excitement for developing responsible machine learning algorithms A documented solid background in either machine learning or statistics Programming experience, in particular including Python The position is part of a collaborative, interdisciplinary project. You thrive in collaboration with others, and you are excited to interact with researchers from different research fields and turn their problems into machine learning. You are ambitious and wish to make a difference in how AI is used in healthcare. You seek to publish your research at top venues, and you are eager to communicate your science broadly to maximize its impact. We offer DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility. Salary and terms of employment The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 2 years, starting June 1 2020 or as soon as possible thereafter. Your workplace will be split between the DTU Lyngby Campus and the Neurobiology Research Unit at Rigshospitalet in Copenhagen. You can read more about career paths at DTU here . Further information Further information may be obtained from Aasa Feragen, tel.: 45 2622 0498, email afhar@dtu.dk . You can read more about the project at http://fairmed.compute.dtu.dk , and you can read more about DTU Compute at www.compute.dtu.dk and aout NRU at www.nru.dk . Application procedure Your complete online application must be submitted no later than 1 May 2021 (Danish time) . To apply, please open the link "Apply online", fill out the online application form. The following must be attached in English: Application (cover letter) CV Academic Diplomas (MSc/PhD) List of publications All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply. DTU Compute DTU Compute is a unique and internationally recognized academic environment spanning the science disciplines mathematics, statistics, computer science, and engineering. We conduct research, teaching and innovation of high international standard—producing new knowledge and technology-based solutions to societal challenges. We have a long-term involvement in applied and interdisciplinary research, big data and data science, artificial intelligence (AI), internet of things (IoT), smart and secure societies, smart manufacturing, and life science. Technology for people DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 12,000 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. Our main campus is in Kgs. Lyngby north of Copenhagen and we have campuses in Roskilde and Ballerup and in Sisimiut in Greenland.
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