Physics of Machine Learning
and Complex Systems
People
The Physics of Machine Learning and Complex Systems group is led by Bert Kappen and Ton Coolen. Both are trained as theoretical physicists, but have over the years worked mostly on applications of mathematical methods from statistical physics and information theory to modelling and inference problems at the interface between physics, biology, data science, computation, and medicine.
Other group members
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based in Nijmegen:
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Dr Wim Wiegerinck - approximate inference, genetic inference and applications
Dr Willem Burgers - Bayesian methods for inference and optimization
Dr Eduardo Dominguez - quantum machine learning
Onno Huijgen - quantum Boltzmann machines
Yannick Lingelman - sensori motor control
Emanuele Massa - regression in the overfitting regime
Jasper Hof - recurrent event models for linking genetic variation to bladder cancer outcomes
Dr Theodore Nikoletopoulos - predictive regression from longitudinal data
Dr Marianne Jonker (RUMC collaborator) -- medical statistics
Dr Hassan Pazira -- medical statistics
Enrico Schmitz -- data science
Mauricio Diaz-Ortiz -- survival analysis for competing risks
Shakeeb Majid - survival analysis with longitudinal covariates
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based in the UK:
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Dr Fabrizio Antenucci - Inference for high-dimensional and longitudinal data
Dr Mark Rowley - Bayesian latent class models and computational implementations
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Master students presently doing projects in Ton's team:
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Menno van der Ster, Paula Koenders, Lauren Keizer, Floris Olthuis, Maria Kokou
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Partner organizations
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SNN (Dutch Foundation for Neural Networks)
Saddle Point Science Europe BV
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Recruitment
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We are currently involved in several projects and grant applications, and plan to grow the group over the coming years. Openings will be posted here. Should you be interested in working in our group as a PhD student or postdoctoral researcher, either in one of our present research areas or in a related area - our interests are broad - then feel free to discuss possible opportunities informally with Bert or Ton.
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Opening: Assistant/Associate Professor of Theoretical Biophysics and Machine Learning
(deadline for applications: March 28th 2024)
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