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Fully funded PhD position on machine learning for scientific computing at Stony Brook University

A fully supported PhD position with an emphasis on machine learning and scientific computing is available in the Civil Engineering Department at Stony Brook University under the guidance of Dr. Georgios Moutsanidis. The desired start date is Fall 2021. 

 

Machine learning techniques have proven to be very powerful in enhancing or even replacing traditional numerical methods. A highly motivated and talented candidate is sought for developing novel and efficient techniques that combine ML and scientific computing, and applying them to the following problems:

 

1)    Extreme events modeling

2)    Fluid-Structure interaction

3)    Hypersonic flows

4)    Additive manufacturing

 

Required Qualifications:

 

1)  Masters and B.Sc. degrees in Engineering or Applied Mathematics with an excellent overall academic record.

2)    Strong background in the Finite Element Method and its application to solid or fluid mechanics.

3)    Strong background in modern machine learning methods and open source packages (e.g. tensorflow, etc.).

4)    Experience with coding in one of the following programming languages: C/C++, Python, Java.

 

The interested applicants should submit an online application at https://www.stonybrook.edu/commcms/civileng/graduate/generalinformation.php. The deadline is January 15th. However, the interested applicants are highly encouraged to first communicate their interest to Dr. Moutsanidis and submit the following material via email at georgios.moutsanidis@stonybrook.edu

 

1)    Transcripts of graduate and undergraduate degrees.

2)    CV

3)    Contact information of at least 3 faculty members that can provide letters of recommendation.

4)    Any relevant publications.

5)    Results of GRE and TOEFL if available.

 

 

 

Due to the current pandemic situation, US citizens, permanent residents, and applicants already in the US, will be given priority.

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