Deep Learning Researcher

Origen.

AI , an artificial intelligence startup focusing on the energy sector, is looking for one or several (senior) Deep Learning Researchers specializing in physics-informed neural networks (PINNs) to join our team in our offices in Hoboken, New Jersey. Origen.

AI has developed cutting edge technology in this sector, solving significant challenges of differential equations for PINNs, such as Buckley Leverett. Currently the Ori Gen team is expanding PINNs for real problems such as fluid dynamics in porous media or CO2 sequestration.

We are creating a passionate and engaging culture that combines cutting-edge research and product-led engineering to provide a supportive balance of structure and flexibility. We are looking for colleagues passionate about bringing cutting-edge AI to industrial problems.

We are willing to hire both on the senior level and at a more intermediate level, depending on the level of experience of the best candidates.

Inventing and refining deep learning methods for predicting geophysical dynamics, with a current focus heavily towards particular oil reservoir dynamics.

Interfacing with the software engineering team who are continuously enhancing our PROTEUS platform for our customers in the energy sector.

Working closely with a research with a high impact in applied deep learning.

An intellectually challenging set of problems

An opportunity to perform cutting edge AI research on problems of critical importance for our future

Colleagues with deep knowledge of the method and domain

Excellent opportunities to grow with the company as we scale up

Stock options

Opportunities to publish and patent

Leading research in one of the most promising startup in USA

Strong knowledge of deep learning methods

Experience with physics-informed neural networks problem

Experience creating deep neural network with parallel GPUs

Experience 3+ in Python, C++,

Experience 3+ with deep learning libraries such as pytorch or tensor flow

Published papers within deep learning, or machine learning generally

Published papers within deep learning in applied areas in physics-informed neural networks

Ability to communicate your ideas clearly and work in teams

Familiarity with engineering physics or mechanical engineering

Design, implement and evaluate models, agents and software prototypes of perceptual processing

Report and present research findings and developments (including status and results) clearly and efficiently, both internally and externally, verbally and in writing

Suggest and engage in team collaborations to meet ambitious research goals

Minimum Qualifications:

PhD or equivalent practical experience

Preferred Qualifications

PhD in machine learning, neuroscience, or computer science

Relevant publications in physics-informed neural networks

Experience with coding GPUs (CUDA)

Relevant experience to the position, such as post doctoral roles, a proven track record of publications, or deep neural network architectures

A real passion for AI

Excellent communication skills in English

Does this role sound like a good fit? Please apply below:

Complete the survey in the application link

Attach your most recent CV in PDF format

Send along links that best showcase the relevant things you’ve built and done