[JOB] 2 Stats/ML Postdoc positions at National University of Singapore (NUS)
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Alexandre Thiery
May 26, 2024, 11:09:15 AMMay 26
to Machine Learning News
Dear All,
Two Postdoctoral Research Fellow positions are available in the Department of Statistics & Data Science at the National University of Singapore (NUS). These positions are offered on a two-year contract basis, with the possibility of renewal subject to review.
Although the research themes are flexible, our primary focus is on the design and analysis of statistical methods for data assimilation of high-dimensional time-series data and generative modeling. With the recent advances in diffusion-based models, concepts initially developed for the inference of time series and in the control theory literature can now be adapted for generative models. Conversely, the latest methodological developments in generative models (e.g., denoising diffusion, stochastic interpolants, flow-methods) can be applied to enhance the performance of traditional statistical tools used in data assimilation for high-dimensional time series models (e.g., ensemble Kalman filters, particle filters). In this project, we propose to explore the intersection of these two areas, aiming to enhance the robustness and accuracy of methods for data-assimilation of high-dimensional dynamical systems, as well as to develop new sampling algorithms.
Details:
Requirements:
Ideal candidates should have:
Contact:
Queries about this post should be addressed to Alex Thiery at a.h.t...@nus.edu.sg. We highly encouraged prospective applicants to get in touch informally to discuss further details about the position first. This project is in collaboration with Jeremy Heng.
The positions will remain open until we find the right candidates.
Link to Position Description: https://alexxthiery.github.io/jobs/2024_diffusion/2024_diffusion.html
Two Postdoctoral Research Fellow positions are available in the Department of Statistics & Data Science at the National University of Singapore (NUS). These positions are offered on a two-year contract basis, with the possibility of renewal subject to review.
Although the research themes are flexible, our primary focus is on the design and analysis of statistical methods for data assimilation of high-dimensional time-series data and generative modeling. With the recent advances in diffusion-based models, concepts initially developed for the inference of time series and in the control theory literature can now be adapted for generative models. Conversely, the latest methodological developments in generative models (e.g., denoising diffusion, stochastic interpolants, flow-methods) can be applied to enhance the performance of traditional statistical tools used in data assimilation for high-dimensional time series models (e.g., ensemble Kalman filters, particle filters). In this project, we propose to explore the intersection of these two areas, aiming to enhance the robustness and accuracy of methods for data-assimilation of high-dimensional dynamical systems, as well as to develop new sampling algorithms.
Details:
- Start Date: Immediate
- Duration: 2 years (Renewable for up to an additional year)
- Salary Range: S$ 70k-90k / Year, plus additional benefits
Requirements:
Ideal candidates should have:
- a Ph.D. in Statistics, Computer Science, Physics, or a closely related field.
- strong experience in Python programming.
- experience with at least one deep-learning framework
- a demonstrated record of academic publications
- research experience that aligns with the core focus of the research programme.
Contact:
Queries about this post should be addressed to Alex Thiery at a.h.t...@nus.edu.sg. We highly encouraged prospective applicants to get in touch informally to discuss further details about the position first. This project is in collaboration with Jeremy Heng.
The positions will remain open until we find the right candidates.
Link to Position Description: https://alexxthiery.github.io/jobs/2024_diffusion/2024_diffusion.html
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