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Open nowPosted 143 days ago

[Residency/Postdoc] Research Scientist - Scientific Foundation Model

LG AI Research37 open roles

Where
Gangseo-gu, Seoul, South Korea
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Your applicationOpen now[Residency/Postdoc] Research Scientist - Scientific Foundation ModelLG AI Research · Gangseo-gu, Seoul, South Korea

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

13.9% of postings close within 7 days. Measured by our own scanner across the market. LG AI Research postings stay open a median of 43 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.9%7 days
  4. 22.4%14 days
  5. 38.1%30 days
  6. 59.0%60 days
This job: posted 143 days ago

LG AI Research median: 43 days open

The posting

팀 소개

Materials Intelligence Lab은 AI를 활용하여 차세대 신소재를 개발하는 연구 조직입니다. 우리는 머신러닝과 시뮬레이션을 결합하여 새로운 소재를 빠르게 탐색하고 설계하는 것을 목표로 합니다.

현재 MI Lab은 다양한 소재 데이터를 학습하여 유기·무기 소재 전반에 대한 물성을 예측할 수 있는 Materials Foundation Model을 개발하고 있습니다. 이를 위해 대규모 데이터셋 구축, 최신 AI 아키텍처 연구, 대규모 모델 학습 및 평가를 함께 수행할 연구자를 찾고 있습니다. AI 기술을 활용하여 실제 과학 문제를 해결하고, 차세대 Scientific Foundation Model 개발에 도전하고 싶은 분들의 지원을 기다립니다.

수행 업무

  • 유기·무기 소재를 통합적으로 다룰 수 있는 Materials Foundation Model 개발
  • 대규모 재료 데이터셋 구축 및 전처리
  • Graph Neural Network(GNN), Transformer 등 최신 아키텍처 연구 및 적용
  • 대규모 학습 파이프라인 구축 및 운영
  • 최신 AI 및 Scientific Machine Learning 논문 분석 및 구현
  • 모델 성능 평가 및 벤치마크 수행
  • 국제 학회 및 저널 논문 작성

계약 형태

  • Residency 또는 Postdoctoral 포지션 1년 계약

지원자격

  • 관련 분야 석사/박사 졸업자(예정자) 및 경력자
  • Machine Learning 연구 또는 개발 경험
  • 딥러닝 프레임워크(PyTorch, JAX 등) 활용 경험
  • 최신 머신러닝 논문을 읽고 구현할 수 있는 역량
  • Deep Learning, Representation Learning, Graph Learning 등 최신 AI 방법론을 이해하고 활용할 수 있는 역량
  • 1년 계약으로 Full Time 근무가 가능하신 분

우대사항

  • Scientific Machine Learning, Geometric Deep Learning 또는 Foundation Model 연구 경험
  • Graph Neural Networks(GNN), Transformer, Equivariant Model 연구 경험
  • 대규모 그래프 데이터 처리 경험
  • NequIP, MACE, MatterSim, CHGNet, SevenNet 등 최신 MLIP 프레임워크 활용 경험
  • ICML, NeurIPS, ICLR, AAAI 및 Domain Journal 등 분야 주요 학회 및 저널 논문 실적
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