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Research Scientist Intern, Alignment - Brain and AI (PhD) (Paris) Job Opening In Paris – Now Hiring Meta

Research Scientist Intern, Alignment Brain and AI (PhD) (Paris)

    France Jobs Expertini Expertini › France › Jobs › Paris › Other General › Research Scientist Intern, Alignment Brain And Ai (Phd) (Paris)

Job description

**Summary:**
Meta was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another.

With over a billion people using the service and more than fifty offices around the globe, a career at Meta offers countless ways to make an impact in a fast growing organization.We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world.

We are seeking individuals passionate in areas such as deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, and applied mathematics and computational neuroscience.

Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale.The mission of Meta FAIR's Brain and AI is to interface neuroscience and artificial intelligence, to both better understand how the brain functions in light of state-of-the-art AI models and to improve AI in light of neuroscientific principles.

We explore, design, and build AI systems at scale to enable next-generation AI technologies.Our internships are twelve (12) to sixteen (16), or twenty-four (24) weeks long and we have various start dates throughout the year.
**Required Skills:**
Research Scientist Intern, Alignment - Brain and AI (PhD) (Paris) Responsibilities:
1.

Develop novel state-of-the-art reinforcement learning, natural language and computer vision algorithms and corresponding systems, leveraging various deep learning techniques.
2.

Analyze and improve efficiency, scalability, and stability of pretraining, encoding and decoding models
3.

Perform state of the art research to advance the science and technology of Machine Learning and Artificial Intelligence applied to neural time series.
4.

Devise better data-driven models for information retrieval, Multi-modal fusion, generation or media understanding (CV, NLP, Speech/ Audio).
5.

Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
6.

Contribute to research that can be applied to Meta Product development.
**Minimum Qualifications:**
Minimum Qualifications:
7.

Currently has or is in the process of obtaining a Ph.D. degree in Machine Learning, Artificial Intelligence, Computer Science, Information or Multimedia Retrieval, Reinforcement Learning, Mathematics and neuroscience[additional], or relevant technical field
8.

Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment
9.

Experience with Python, C++, C, Java or other related language
10.

Experience with deep learning frameworks such as Pytorch or Tensorflow
11.

Experience building systems based on machine learning and/or deep learning methods
12.

Research experience with algorithms for sequential decision-making, e.g., planning, reinforcement learning, or similar
**Preferred Qualifications:**
Preferred Qualifications:
13.

Intent to return to degree program after the completion of the internship/co-op
14.

Experience in encoding, decoding or pretraining of large scale algorithms applied to neural time series (functional imaging or electrophysiology)
15.

Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICLR, AAAI, RecSys, KDD, IJCAI, CVPR, ECCV, ACL, NAACL, EACL, ICASSP, or similar
16.

Demonstrated experience and self-driven motivation in solving analytical problems using quantitative approaches
17.

ML/ AI research and/ or work experience in information retrieval problems, generative approaches, and/ or Natural Language Processing, CV, or Speech/ Audio
18.

Experience building systems based on machine learning, reinforcement learning and/or deep learning methods
19.

Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
20.

Experience working and communicating cross functionally in a team environment
**Industry:** Internet

Required Skill Profession

Other General


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