This job has expired on Indeed
Reasons could include: the employer is not accepting applications, is not actively hiring, or is reviewing applications

Postdoctoral Researcher/Research Scientist - Machine Learning

New York Structural Biology Center
89 Convent Ave, New York, NY 10027
Remote
$70,000 - $130,000 a year - Full-time

Location

89 Convent Ave, New York, NY 10027

Benefits
Pulled from the full job description

  • 401(k)
  • Dental insurance
  • Flexible schedule
  • Health insurance
  • Paid time off
  • Relocation assistance
  • Retirement plan

Full job description

Simons Machine Learning Center at the New York Structural Biology Center

The Simons Machine Learning Center (SMLC) is a new Simons Foundation funded initiative that is part of the Simons Electron Microscopy Center at the New York Structural Biology Center in New York, NY. Machine learning is transforming structural biology from data collection and structure determination to structure and function prediction. At the SMLC, our mission is to develop machine learning algorithms and software for understanding the structures of biological molecules. We are building a team of machine learning, computer vision, and computational biology experts to push the boundaries of machine learning and structural biology. As part of NYSBC, we have unprecedented access to state-of-the-art instruments (including electron microscopes, NMR, and X-ray), technologists, and structural biologists. We are well-funded and growing quickly.

Job Description

We are looking for a Postdoc or Research Scientist to join SMLC to develop machine learning and computer vision methods for analyzing cryo-EM and cryo-ET data. Problems of interest include reconstructing protein structures from cryoEM images, deep learning methods for object detection and instance and semantic segmentation, and unsupervised and data efficient methods. Candidates interested in other aspects of structural and protein biology, particularly protein structure prediction and generative modeling, will also be considered. Applicants should have a strong quantitative background with coding experience, be interested in structural biology applications, and be motivated to learn. Good communication skills and the ability to work independently are musts.

Candidates should expect to:

  • Invent and implement new machine learning algorithms for addressing diverse problems in computer vision with application to structural biology and cryo-electron microscopy
  • Conduct experiments and analyses
  • Collaborate with experimentalists and hardware technologists
  • Publish and present findings at machine learning, computational biology, and/or structural biology venues

Requirements

  • PhD in computer science, computational biology/bioinformatics, statistics, physics, or other similar quantitative fields
  • Strong coding ability. Experience with machine learning and linear algebra libraries (e.g. numpy, pytorch, tensorflow) is a plus
  • Experience working with protein structure data is a plus
  • Experience with high performance computing/GPU computing is a plus
  • Research experience in machine learning, computer vision, natural language processing, bioinformatics, or other related fields
  • Ability to work independently, motivated to learn
  • Strong communication skills

Benefits at NYSBC

  • Access to significant compute resources and state-of-the-art instruments including 7 Titan Krios microscopes
  • Well funded group with plenty of GPU compute
  • Located in NYC, remote work is optional
  • Competitive salary
  • Generous retirement package
  • Medical and dental coverage

Job Type: Full-time

Salary: $70,000.00 - $130,000.00 per year

Benefits:

  • 401(k)
  • Dental insurance
  • Flexible schedule
  • Health insurance
  • Paid time off
  • Relocation assistance
  • Retirement plan

Schedule:

  • Monday to Friday

Ability to commute/relocate:

  • New York, NY 10027: Reliably commute or willing to relocate with an employer-provided relocation package (Preferred)

Education:

  • Doctorate (Required)

Work Remotely:

  • Yes