Postdoc Position to work in the project “Bias and Fairness in Medicine” at DTU Compute, Technical University of Denmark (Postdoctoral Researcher Position, Machine Learning in Medicine, Computer Science Jobs)
Deadline to Apply
May 01, 2021 (23: 59 GMT +1)
|Position||Postdoctoral Researcher Position|
|No. of Position(s)||1|
|Research Area||– Computer science|
– Machine Learning
|Salary||According to Standard Norms|
DTU Lyngby Campus
|Contract Period||2 Year|
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
Responsibilities/ Job Description
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.
- 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.
You will also be affiliated with the Neurobiology Research Unit (NRU) at Rigshospitalet, a cross-disciplinary research center focusing on brain neurobiology and advanced data analytic approaches of neuroimaging data
How to Apply?
To apply, please open the link “Apply online”, fill out the online application form.
The following must be attached in English:
- Application (cover letter)
- Academic Diplomas (MSc/PhD)
- List of publications
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.
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
- 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.
- All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply.
- 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.
Tel.: +82-45 2622 0498
Post expires at 8:59am on Sunday May 2nd, 2021 (GMT+9)