machine learning

Join us at the Department of Electrical and Computer Engineering at Aarhus University for a two-year postdoctoral position focused on physics-driven machine learning for ground-based, airborne, and drone-based transient electromagnetic (TEM) data. The project will build on anEMone, our fully differentiable TEM forward-modelling framework implemented in PyTorch, to develop supervised and self-supervised deep learning models that directly incorporate electromagnetic physics.

A fully funded PhD position is available at the Department of Mechanics and Materials, Faculty of Transportation Sciences, Czech Technical University in Prague (CTU), Czech Republic, within the international PICTUS doctoral fellowship programme.

Fully funded postdoc position 

Ponkrshnan Thiagarajan, Susanta Ghosh, "Jensen–Shannon divergence based novel loss functions for Bayesian neural networks", Neurocomputing, 2024, 129115, ISSN 0925-2312.  https://doi.org/10.1016/j.neucom.2024.129115  

Highlights

Blue Halo, in support of the US Air Force Research Laboratory (AFRL), has multiple exciting postdoc opportunities in computational mechanics (available to US citizens). Interested candidates should visit the link(s) below for more information, and to send their CV / cover letter.

The Mechanics of Functional Ceramics group (https://faculty.hitsz.edu.cn/yanzilin) at HITsz, led by Dr. Zilin Yan, Associate Professor, is seeking highly motivated Ph.D. students  in the following areas.

We invite applications for post-doctoral researcher positions in uncertainty quantification, multiphysics simulation and structural optimization for metal additive manufacturing processes. 

Postdoc Opening in Computational Materials Research

Qualifications:

o   Ph.D. in Mechanical Engineering or related fields

o   Proficiency in finite element modeling and simulation

o   Substantial experience with computational mechanics, fracture mechanics, and machine learning

o   Strong abilities in code development and use finite element software packages

Dera iMechanica Community,

Below is information about a short course I will be offering at MIT this summer, in Live Virtual format: Machine Learning for Materials Informatics (Jul 29 - Aug 2, 2024).  This is an exciting opportunity that will cover fundamentals and applications in the emerging space of AI/ML for engineering, featuring hands-on interactive code development in Jupyter notebooks. We'll do a deep dive into all critical tools from autoencoders to graph neural nets to multimodal LLMs and multi-agent modeling. Please reach out to me if you have any questions.

The Mechanics of Functional Ceramics group (http://faculty.hitsz.edu.cn/yanzilin?lang=en) at HITsz, led by Dr. Zilin Yan, Associate Professor, is seeking highly motivated postdoctoral researchers and Ph.D. students for three directions.