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Temporary Machine Learning Postdoc Jobs in Pennsylvania

A postdoctoral scholar position is available in the Computational Electromagnetics and Antennas ... using Machine Learning based multi-physics tools for predictive modeling, high-dimensional ...

... postdoctoral or equivalent research experience demonstrating an independent record of publication in applied machine learning, computer vision, and/or scientific data analysis. Experience with one or ...

... postdoctoral scholar ... The position will involve machine learning for autonomous thin-film materials synthesis by ...

A strong background in artificial intelligence, machine learning, computational science, data ... For Postdoctoral benefits, please see our Postdoctoral Benefits page.) CAMPUS SECURITY CRIME ...

Develop progressive flow-physics-learning and machine-learning methods * Perform CFD simulations ... For Postdoctoral benefits, please see our Postdoctoral Benefits page.) CAMPUS SECURITY CRIME ...

... Postdoctoral Scholar beginning January 2027. The successful candidate will work with Professor ... methods in machine learning.These include applications of Random Matrix theory and Gaussian ...

Ce postdoc a pour objectif d'etendre les travaux du post doc precedant : Explorer les sujets ... Notre accord temps de travail pour preserver votre equilibre vie professionnelle / vie privee avec ...

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Temporary Machine Learning Postdoc information

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 skills and qualifications are needed to thrive as a temporary machine learning postdoc?

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?

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 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 the most commonly searched types of Machine Learning Postdoc jobs in Pennsylvania?

The most popular types of Machine Learning Postdoc jobs in Pennsylvania are:

What are popular job titles related to Temporary Machine Learning Postdoc jobs in Pennsylvania?

For Temporary Machine Learning Postdoc jobs in Pennsylvania, the most frequently searched job titles are:

What job categories do people searching Temporary Machine Learning Postdoc jobs in Pennsylvania look for?

The top searched job categories for Temporary Machine Learning Postdoc jobs in Pennsylvania are:

What cities in Pennsylvania are hiring for Temporary Machine Learning Postdoc jobs?

Cities in Pennsylvania with the most Temporary Machine Learning Postdoc job openings:

Postdoctoral Research Associate - Yttri Lab

Pittsburgh, PA • On-site

Carnegie Mellon University
Colleges, Universities, and Professional Schools • 1 - 10 employees

Full-time

Re-posted 22 days ago


Carnegie Mellon University rating

8.8

Company rating: 8.8 out of 10

Based on 25 frontline employees who took The Breakroom Quiz


Job description

Description
The Yttri lab at Carnegie Mellon University is looking for a talented postdoctoral associate to interrogate the circuit dynamics underlying naturalistic behavior. Building off our unsupervised algorithm for segmenting behaviors from video (Hsu and Yttri, Nature Communications), we are looking to explore the interactions between multiple brain areas over long time scales (weeks) as mice navigate their arena and/or learn new tasks. Several avenues are open to research, including interrogation of timescales of representation, plasticity, and circuit dynamics in normal mice and disease models. Eric and the lab are committed to building a supportive community for inquiry and curiosity that foster members to become better scientists and people.
Qualifications
PhD or MD, background in neuroscience or statistical methods. Background in population-level analysis of neural data and/or basic machine learning principles required, but needn't have been applied to rodent studies.
Application Instructions
Applications, including a cover letter and a curriculum vitae indicating your interest and relevant training should be submitted electronically via Interfolio.

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