The Dutch national research institute for mathematics and computer science (CWI,
Centrum Wiskunde & Informatica) located in Amsterdam, The Netherlands has a
vacancy for a TENURE TRACK POSITION on AI for Life Sciences and Health.
Furthermore, together with the Leiden University Medical Center (LUMC), CWI has
2 FULLY FUNDED PhD POSITIONS on a joint project on the development of
evolutionary machine learning techniques for explainable AI and their
application to medical data.
The closing date for each of these vacancies is March 1, 2020.
https://www.cwi.nl/jobs/vacancies/tenure-track-position-artificial-intelligence-for-life-sciences-and-health
https://www.cwi.nl/jobs/vacancies/ph-d-students-on-a-joint-project-on-the-development-of-evolutionary-machine-learning-techniques-for-explainable-ai-and-their-application-to-medical-data
Each PI in the CWI Life Sciences and Health (LSH) research group has a
fundamental research focus rooted within a subdiscipline of computer science and
mathematics. Within their area of expertise, they develop and analyze
(theoretically or experimentally) new models and algorithms. The fundamental
backgrounds of our current PIs lie within the areas of evolutionary algorithms,
combinatorial algorithms, and operations research.
Each PI furthermore has a clear focus and intent on developing these models and
algorithms for applications in the LSH domain. To this end, and in striving to
achieve societal impact, we actively collaborate with academic hospitals,
biological and biochemical research institutes, and industry. Presently, our
team of PIs has expertise mainly in decision support for clinical oncology,
computational genomics and phylogenetics, and biological network analysis.
Our group has recently had several successes in the design and application of AI
techniques (which we specifically deem to include Machine Learning (ML)) in the
LSH domain. Combined with the fact that LSH experts recognize more and more that
forms of AI are needed to realize innovations, the present situation provides an
excellent opportunity for our group to grow and expand its horizons.
The LSH group is therefore looking for a researcher with an excellent track
record in computer science or mathematics having a clear focus on AI and a clear
affinity for applications in the LSH domain. The candidate is expected to
establish a highly visible and successful research line on AI for LSH,
complementing and strengthening existing research lines in the LSH group of CWI.
In addition, CWI closely collaborates with LUMC to work on innovations in the
medical domain along the entire spectrum from algorithmic foundations to
clinical integration. Currently, CWI (the Life Sciences and Health research
group) and LUMC (the department of radiation oncology) have a joint project for
which we seek 2 talented PhD students (one to be hired at CWI and one to be
hired at LUMC) to work together on new techniques for and novel combinations of
evolutionary algorithms and machine learning, in a project funded by the Dutch
Research Council (NWO, Nederlandse Organisatie voor Wetenschappelijk Onderzoek)
entitled "EXAMINE - Evolutionary eXplainable Artificial Medical INtelligence
Engine".
Machine learning (ML), especially deep learning, has shown to be capable of
impressive results in many fields of science and society. Nevertheless, in most
cases, learned models are still incomprehensible black boxes for humans.
Especially for disciplines such as medicine, this is a bottleneck for widespread
adoption, because for clinical use, medical experts want to understand what has
been learned and why.
We will therefore focus on types of ML that provide models that can be
insightfully inspected and understood. Specifically, these models are made up of
(combinations of) symbolic expressions, deep neural networks for medical images
and radiation dose distributions (used for treating cancer), and Bayesian
networks that can be used to create explainable prediction models (e.g., of
treatment outcomes).
To learn such explainable models, powerful and versatile optimization algorithms
are required. For this, we will innovate the recently introduced
state-of-the-art research line on model-based evolutionary algorithms known as
the Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) family and exploit
recently published new insights into its (GPU) parallelization capabilities.
The intention is that both PhD students will work on novel combinations of
evolutionary algorithms and machine learning. However, one PhD student is
intended to focus more on symbolic expression evolution and the other on deep
neural network evolution. The students are furthermore expected to work together
on integrating their results with Bayesian network evolution and to perform
clinical validation studies using data of gynaecological cancer patients.
Candidates are therefore expected to spend at least one day per week at the
other institute.
For more information about the vacancies, please contact Peter A.N. Bosman,
[log in to unmask] and/or visit the following links:
https://www.cwi.nl/jobs/vacancies/tenure-track-position-artificial-intelligence-for-life-sciences-and-health
https://www.cwi.nl/jobs/vacancies/ph-d-students-on-a-joint-project-on-the-development-of-evolutionary-machine-learning-techniques-for-explainable-ai-and-their-application-to-medical-data
-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
Prof.dr. Peter A.N. Bosman
Senior Researcher at Centrum Wiskunde & Informatica (CWI)
(Dutch National Research Institute for Mathematics and Computer Science)
Life Sciences and Health Research Group
Professor of Evolutionary Algorithms at Delft University of Technology
Algorithmics Section of the Department of Software Technology
Faculty of Electrical Engineering, Mathematics and Computer Science
E [log in to unmask] W http://homepages.cwi.nl/~bosman T +31(0)205924265
-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
########################################################################
To unsubscribe from the EVOLUTIONARY-COMPUTING list, click the following link:
https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=EVOLUTIONARY-COMPUTING&A=1
|