machine learning

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.

I have an opening in my group for a 2-year postdoc position offering applicants an exciting opportunity to join my ERC-funded project “ALPS - AI-based Learning for Physical Simulation”.

Job description

You will be contributing to developing novel algorithms at the intersection of computational physics and machine learning for the automatic identification of symbolic models of physical systems starting from experimental data.

The DoD HPC Modernization Program has high-performance computing internship opportunities at the Air Force Research Laboratory. These internships give undergraduate and graduate students the opportunity to perform scientific, computational research alongside AFRL researchers in support of the US Air Force’s mission.

Hanxun Jin (a,b), Horacio D. Espinosa (b)
a Division of Engineering and Applied Science, California Institute of Technology
b Department of Mechanical Engineering, Northwestern University

In recent years, Machine Learning (ML) has become increasingly prominent in Solid Mechanics. Its diverse applications include extracting unknown material parameters, developing surrogate models for constitutive modeling, advancing multiscale modeling, and designing architected materials. In this Journal Club, we will focus our discussion on the recent advances and challenges of ML when experimental data is involved. With broad community interest, as reflected by the increasing number of publications in this field, we have recently published a review article in Applied Mechanics Reviews titled “Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review”. Moreover, a recent insightful paper from Prof. Sam Daly’s group also discussed some perspectives in this field. In this Journal Club, we would like to introduce and share insights into this exciting field.

Extreme Mechanics Letters (EML) Special Issue: Call for Paper 

Machine Learning and Mechanics

We are looking for a postdoctoral researcher to work on the project MECA-ICTUS, a 3-year project funded under the Generación de Conocimiento 2022 call of Agencia Estatal de Investigación. In MECA-ICTUS we will pursue the development of computational mechanics and machine learning tools for predicting the success of endovascular thrombectomy, an urgent intervention for the removal of thrombi in Acute Ischemic Stroke Patients.

Multiple postdoc and one PhD positions are open at Tsinghua University. The research will take place at Tsinghua University’s Shenzhen International Graduate School (SIGS), located in Shenzhen, China, and is partly sponsored by NSFC and Tsinghua SIGS’s scientific research startup funds.

We invite applications for post-doctoral and Ph.D. positions in machine learning, multi-physics simulation and uncertainty qualification for additive manufacturing processes. 

For additional information, please contact Prof. Xiaoping Qian (qian@engr.wisc.edu). To apply, email your application files (CV, 1-page summary of research accomplishments and research interests, and 3 references).

The Uncertainty Quantification (UQ) Lab at the University of Houston (UH), led by Dr. Ruda Zhang, invites applications for:

• two (2) PhD student positions in areas of data-driven engineering and uncertainty quantification, and
• one (1) postdoctoral researcher in areas of surrogate modeling and data-driven dynamics.

For job details and updates, see lab webpage: https://uq.uh.edu/positions

 PhD Students - 2023

Joining: https://wwwfr.uni.lu/formations/fstm/doctoral_programme_in_computational...

PhD candidate on Machine Learning applied to Critical Zone sciences 

Ph.D. positions are available at the Multiscale Material Modeling Lab at the University of North Carolina at Charlotte. The Ph.D. students will develop and use tools such as machine learning, finite elements, and molecular dynamics to study the mechanical properties of materials. Candidates with a strong background and interest in solid mechanics, programming, and computational solid mechanics are encouraged to submit their CV to atabarra@uncc.edu. In your CV please include the name and contact information of three references.  

Dr. Lei Wang’s research group at the University of Cincinnati (UC) is seeking two high-motivated and talented PhD students to be appointed as Graduate Assistants to conduct geotechnical engineering research in the Department of Civil and Architectural Engineering and Construction Management, beginning January 2023 or August 2023. 

I would like to draw your attention to our recently proposed predictive method based on a semi-empirical model (LEFM) and Neural Network, exploiting the Physics-informed Machine Learning concept. We show how the accuracy of state-of-the-art fatigue predictive models, based on defects present in materials, can be significantly boosted by accounting for additional morphological features via Physics-Informed Machine Learning.

Join the Simpleware Product Group at Synopsys and nTopology for a webinar this month on automated segmentation and design workflows for patient-specific surgical guides.

Learn more and register for this free event here: https://register.gotowebinar.com/register/3232312822632785679?source=iMe...

I am seeking a motivated and qualified postdoctoral fellow with expertise in the field of machine learning (ML)-informed materials design. In particular, the postdoctoral fellow will work closely in collaboration with other experimentalists and modelers within the newly established AI for Materials Design (AIMD) facility at JHU for the design of new refractory multi-principal-element alloys (RMPEAs) by identifying their processing-structure-property-performance relationships for high-strain-rate and high-temperature-rate applications.

Synopsys are running a webinar this month on using AI medical image segmentation in Simpleware software to scale-up patient-specific workflows, save time, and free up staff resources. Highly recommended if you haven't yet had a chance to review the tools in Simpleware software.

Register here: https://register.gotowebinar.com/register/4951806069167092496?source=iMe...

Over the past several years, machine learning (ML) applied to problems in mechanics has massively grown in popularity. Here is a figure from a slide that I made in early 2020 referencing a few examples from the literature — already this slide feels out of date! All of these authors (and many many others) have published new papers on this topic. 

Structural Integrity and MEchanical Design (SIMED) group is seeking a 1-year full-time Postdoctoral Researcher in Machine Learning applied to fracture mechanics. The successful applicant will work at the Polytechnic Engineering and Architecture Department (DPIA) of the University of Udine, under Dr Enrico Salvati’s supervision.

Two postdoc positions in computational science are available at UIUC in the research group of Prof. Harley T. Johnson in the Department of Mechanical Science and Engineering and the Materials Research Lab.  

4 fully-funded PhDs are available in Delft University of Technology under the joint supervision of researchers from the Faculty of Aerospace Engineering and the Faculty of Electrical Engineering, Mathematics and Computer Science. We will explore the exciting interdisciplinary areas of Quantum Computing and M

Applications are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Agroecology programme. The position is available from 1st February 2022 or later.