machine learning

Applications are invited for PhD positions at the Algorithms in Medicine and Neuro-Technology Lab (AIMAN Lab) in the Department of Mechanical Engineering at George Mason University, Fairfax, VA. "Research" The AIMAN Lab pursues fundamental breakthroughs in biomedical cyber-physical systems.

<p class="MsoNormal" style="text-align: center;" align="center"><span style="text-align: start;">Applications are invited for PhD positions at the Algorithms in Medicine and Neuro-Technology Lab (AIMAN Lab) in the Department of Mechanical Engineering at George Mason University, Fairfax, VA. "Research" The AIMAN Lab pursues fundamental breakthroughs in biomedical cyber-physical systems.

Applications are invited for PhD positions at the Algorithms in Medicine and Neuro-Technology Lab (AIMAN Lab) in the Department of Mechanical Engineering at George Mason University, Fairfax, VA.

Research
The AIMAN Lab pursues fundamental breakthroughs in biomedical cyber-physical systems. The lab’s primary research focuses on application of mathematical modeling, controls and estimation theory, and machine learning in health information technology including decision support and automated care systems, with the intention of improving the quality of healthcare, as well as brain-computer interfaces to bring neuro-enhancements to the daily consumer.

Application
Interested researchers with passion in digital healthcare and neuroscience are encouraged to send their CV to Dr. Ramin Bighamian at rbighami@gmu.edu.

Qualification
Experience in controls engineering, estimation theory, machine learning, MATLAB
A Master's degree in mechanical engineering, electrical engineering, or other related disciplines.

<p>Applications are invited for PhD positions at the Algorithms in Medicine and Neuro-Technology Lab (AIMAN Lab) in the Department of Mechanical Engineering at George Mason University, Fairfax, VA. "Research" The AIMAN Lab pursues fundamental breakthroughs in biomedical cyber-physical systems.

<p><a href="http://hdl.handle.net/10993/38545">http://hdl.handle.net/10993/38545</a>...
<p>Training at the European Commission&nbsp;</p>
<p>Upskilling in Data Science</p>
<p>Enjoy!</p>
<p>Stéphane</p>

https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.121.255304

Accelerated Search and Design of Stretchable Graphene Kirigami Using Machine Learning

P.Z. Hanakata, E.D. Cubuk, D.K. Campbell and H.S. Park

Job Description Requisition Title:Lead Modeling Scientist 

The Department of Electrical Engineering at Stanford University (http://ee.stanford.edu/) invites applications for a tenure-track faculty appointment at the junior level (Assistant or untenured Associate Professor) in the broadly defined field of electrical and computer engineering. The department is especially interested in candidates in robotics, autonomous systems, embedded systems, signal processing, control, optimization, and machine learning.

Dear colleagues, 

Luxembourg FNR is funding 20 PhD students 

https://driven.uni.lu/

Please contact the principal investigators. See attachment.

Regards,

Stéphane P.A. BORDAS

http://legato-team.eu/

Intro

Schlumberger has an opening in Sugar Land, Texas for a Modeling and Simulation Engineer. The Modeling and Simulation Engineer will be responsible for developing digital representations (or twins) of physical assets or processes to produce business outcomes. You will need to work seamlessly with a multidisciplinary team and present project progress to various internal and external clients.

Responsibilities

Title: Modeling and Simulation Engineer

Category: Full-time position in industry

Employer: Schlumberger Technology Corporation

Location: United States, Texas, Sugar Land

Opening Date: 8/1/2018

Job Description

The Stout Infrastructure, Geotechnics, and Materials (SIGMa) Lab at Howard University, Washington, DC, invites applicants for a Master's position in optimization for Fall 2018. Highly-motivated, industrious individuals with a strong background in programming, geotechnics and structural analysis, adequate English proficiency, and the ability to work both independently and as part of a collaborative team are encouraged to apply.

Required qualifications 

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MS27: Computational GeomechanicsWaiChing Sun, Columbia University
Jose Andrade, Caltech
Ronaldo Borja, Stanford University
Jinhyun Choo, University of Hong Kong
Majid Manzari, George Washington University
Richard Regueiro, University of Colorado Boulder

Title: Modeling and Simulation Engineer

Category: Full-time position in industry

Employer: Schlumberger Technology Corporation

Location: United States, Texas, Sugar Land

Opening Date: 12/01/2017

Job Description

Dear colleagues,

We encourage you to submit your abstracts to minisymposium 1801 of the 13th World Congress on Computational Mechanics (New York City, from July 22 to 27 of 2018). This minisymposium focuses on:

1. recently developed methods for data-driven approaches;

2. data-driven applications to fluids, structures and materials involving (but not limited to) machine learning, uncertainty quantification and/or optimization.

Hi all,

I  know that the study and application of machine learning/artificial intelligence are somehow popular nowadays, in a general academia. I happen to be interested in that. I found people use this tool to predict crystal structure in material science, to characterize molecule structure in chemistry. The first impression is that the machanince learning helps to deal with the raw data, to constitute empirical models etc. However, there are not as many published works as I imagine, on the application of machine learning in mechanics.

A new perspective on model reduction for nonlinear multi-scale analysis of heterogeneous materials. In this work, we seek meaningful low-dimensional structures hidden in high-dimensional multi-scale data.