Connectionists: Postdoctoral fellow for deep learning applied to 3D printing with biomaterials

[Gemma Roig]

Dear community,

We are excited to announce the postdoc job opening for a new project on developing deep learning models to predict and compensate biomaterial inconsistency in 2D printing. Start date is 1st of July 2019. 

Title: 

Postdoctoral fellow for deep learning applied to 3D printing with biomaterials

Organisation and location: 

Singapore University of Technology and Design (SUTD), Singapore

Description of the job: 

We are seeking a postdoctoral fellow to work on a research project related to deep learning models applied to biomaterial deformation predictions. The PIs of the project include Prof. Javier Fernandez, Prof. Stylianos Dritsas and Prof. Gemma Roig. The position is for one year extendable to 3 years. 

Key requirements for the position: 
- PhD in computer Science, applied mathematics or related fields.
- Strong record of publication record in tier 1 conferences and journals
- Strong knowledge in machine learning (deep learning, RNN, LSTMs) 
- Excellent programming skills in python, and extensive experience in tensorflow, pytorch or related libraries
- Experience in 3D reconstruction and collecting 3D data,
- Interest in biomaterials for 3D printing,
- Knowledge of high performance distributed computing.

Candidates with a hands on, proactive approach and problem-solving skills are strongly encouraged to apply. 
 
Application Instructions: Contact Dr. Gemma Roig, gemmar [at] mit [dot] edu. Include CV, 3 selected publications, grades and email address of at least 1 reference. Please include in the email subject: [SUTD postdoc].

Contact name and contact email: 

Gemma Roig: gemmar at mit.edu <mailto:gemmar at mit.edu>

Best regards,
Gemma


-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20190214/55d834d3/attachment.html>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: smime.p7s
Type: application/pkcs7-signature
Size: 1865 bytes
Desc: not available
URL: <http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20190214/55d834d3/attachment.p7s>