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Temporary Machine Learning Postdoc Jobs in Newark, NJ

Jane Street

Machine Learning Researcher

New York, NY · On-site

An undergraduate, PhD student, or postdoc with practical experience working on ML problems ... Curious about the machine learning landscape and excited to apply state-of-the-art techniques drawn ...

New York University

POSTDOCTORAL ASSOCIATE

New York, NY · On-site

$62K - $67K/yr

Description POSTDOCTORAL ASSOCIATE New York University Tandon School of Engineering NYU Tandon ... Conducting advanced research in machine learning and data analytics for power system operation and ...

Mount Sinai Hospital

Postdoctoral Fellow-MSH

Manhattan, NY · On-site

$53K - $73K/yr

This Postdoctoral Research Fellowship position will focus primarily on using biomedical data science and machine learning methodologies to explore cardiovascular disease phenotypes in the Mount Sinai ...

Nokia

Fiber Sensing PostDoc

Murray Hill, NJ

Preferred 3+ years of professional or postdoctoral technical experience in the field of optical ... Machine Learning : Strong practical experience with state-of-the-art machine learning tools and ...

Mount Sinai Hospital

Postdoctoral Fellow-MSH

Manhattan, NY · On-site

$53K - $73K/yr

A postdoctoral position in bioinformatics/Biostatistics/data science is available at the Icahn ... machine learning to develop predictive models of diagnosis and prognosis, as well as a vehicle to ...

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Temporary Machine Learning Postdoc information

What are the key skills and qualifications needed to thrive as a Temporary Machine Learning Postdoc, and why are they important?

To thrive as a Temporary Machine Learning Postdoc, you need a PhD in a relevant field, a solid grasp of machine learning theory, and strong programming skills (often in Python or R). Experience with tools such as TensorFlow, PyTorch, and high-performance computing environments, as well as a record of peer-reviewed research, is typically required. Strong analytical thinking, collaboration, and effective communication help you stand out in this research-intensive role. These skills are essential for advancing cutting-edge research, publishing impactful findings, and contributing to interdisciplinary projects.

What types of projects and collaborations can a Temporary Machine Learning Postdoc expect to engage in during their appointment?

A Temporary Machine Learning Postdoc typically works on cutting-edge research projects, often contributing to ongoing studies or initiating novel investigations within the field. Collaboration is common, both within their immediate research group and with interdisciplinary teams, such as data scientists, domain experts, or industry partners. Postdocs may also mentor graduate students, present findings at conferences, and publish papers, gaining valuable experience that can lead to academic or industry roles. The environment is fast-paced and research-driven, offering opportunities for professional growth and expanding one's research portfolio.

What is a Temporary Machine Learning Postdoc?

A Temporary Machine Learning Postdoc is a fixed-term research position, typically held at a university or research institution, focused on advancing knowledge and techniques in machine learning. Postdoctoral researchers in this role work on specific projects, often collaborating with faculty, graduate students, or industry partners. The position is designed to provide advanced training and research experience after earning a PhD, usually lasting from several months to a couple of years. Temporary postdocs may contribute to publishing academic papers, developing algorithms, and mentoring students, while preparing for longer-term academic or industry careers.

What is the difference between Temporary Machine Learning Postdoc vs Data Scientist?

AspectTemporary Machine Learning PostdocData Scientist
CredentialsPhD in Computer Science, Data Science, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; often requires experience
Work EnvironmentAcademic or research institutions, labsCorporate, tech companies, startups
Employer & Industry UsageUniversities, research centersBusiness, technology, finance, healthcare
Search & Comparison IntentUnderstanding research-focused roles, academic opportunitiesIndustry roles, applied data analysis, business impact

The Temporary Machine Learning Postdoc is primarily research-oriented, often in academic or research settings, requiring a PhD. In contrast, a Data Scientist typically works in industry, applying data analysis and machine learning to solve business problems, often with a Bachelor's or Master's degree. Both roles involve machine learning skills but differ in environment, focus, and experience level.

What are popular job titles related to Temporary Machine Learning Postdoc jobs in Newark, NJ? For Temporary Machine Learning Postdoc jobs in Newark, NJ, the most frequently searched job titles are:
What job categories do people searching Temporary Machine Learning Postdoc jobs in Newark, NJ look for? The top searched job categories for Temporary Machine Learning Postdoc jobs in Newark, NJ are:
What cities near Newark, NJ are hiring for Temporary Machine Learning Postdoc jobs? Cities near Newark, NJ with the most Temporary Machine Learning Postdoc job openings:
Temporary Machine Learning Postdoc jobs near you
Machine Learning Researcher

Machine Learning Researcher

Jane Street

New York, NY

Other

Re-posted 20 hours ago

Job description

About the Position

Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Researcher while also providing a truly unparalleled educational experience. You'll work side by side with experienced ML Researchers on projects that we've selected for their combination of novel ML ideas and relevance to real-world systematic trading strategies. You'll learn how we think about markets through challenging classes and activities, and practice using established methods alongside our own unique twists to train practical models.

At Jane Street, the lines between research, technology, and trading are intentionally blurry, and you'll have access to petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing thousands of high-end GPUs. Trading poses unusual challenges-large models and nonstationary datasets in a competitive multi-agent environment-that force us to search for novel techniques.

You'll spend the bulk of your internship working closely with full-time machine learning researchers on projects drawn from their own work. You might conduct an end-to-end study of an unexplored dataset, try a new modeling paradigm for a thorny problem, or consider blue-sky approaches that we're still trying to figure out. The problems we work on rarely have clean, definitive answers, and they often require insights from colleagues across the firm with different areas of expertise. Depending on the day, you might be diving deep into market data, tuning hyperparameters, debugging training issues, or analyzing the predictions your model makes.

Note that given the IP-sensitive nature of machine learning research at Jane Street, it is unlikely that any research findings associated with the internship will be suitable for outside academic publication.

About You

If you've never thought about a career in finance, you're in good company. Many of us were in the same position before working here. If you have a curious mind and a passion for solving interesting problems, we have a feeling you'll fit right in. We're more interested in how you think and learn than what you currently know. You should be:

  • An undergraduate, PhD student, or postdoc with practical experience working on ML problems
  • Interested in applying logical and mathematical thinking to all kinds of problems
  • Curious about the machine learning landscape and excited to apply state-of-the-art techniques drawn from many problem domains
  • Fluent with a versatile set of models and tricks 
  • Able to rapidly implement and iterate on your ideas in Python and your favorite ML framework
  • Eager to ask questions, admit mistakes, and learn new things

If you'd like to learn more, you can read about our interview process and meet some of the team. Learn more about Jane Street's internship program here.

Apply