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Temporary Machine Learning Postdoc Jobs in Washington, DC

Imagery Anst Prin

Sterling, VA · On-site

$118K - $200K/yr

Experience in Machine Learning (ML). * A current TS/SCI clearance with ability to obtain CI poly if ... Temporary employees generally are not eligible for BAE Systems benefits, but can elect to ...

Experience in Machine Learning (ML). * A current TS/SCI clearance with ability to obtain CI poly if ... Temporary employees generally are not eligible for BAE Systems benefits, but can elect to ...

... Machine Learning, Infrastructure, and related technical domains * Build and execute proactive ... Pay within range listed above + temporary benefits package (applicable after 60 days of employment ...

... Machine Learning, Infrastructure, and related technical domains * Build and execute proactive ... Pay within range listed above + temporary benefits package (applicable after 60 days of employment ...

General experience in Machine Learning (ML) techniques to EO imagery and data to address ... Temporary employees generally are not eligible for BAE Systems benefits, but can elect to ...

Imagery Anst Sr

Sterling, VA · On-site

$97K - $164K/yr

General experience in Machine Learning (ML) techniques to EO imagery and data to address ... Temporary employees generally are not eligible for BAE Systems benefits, but can elect to ...

... postdoctoral scientist to conduct biomolecular research. The researcher will join a ... machine learning to identify odorant signatures. The position provides the opportunity for ...

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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 the most commonly searched types of Machine Learning Postdoc jobs in Washington, DC? The most popular types of Machine Learning Postdoc jobs in Washington, DC are:
What are popular job titles related to Temporary Machine Learning Postdoc jobs in Washington, DC? For Temporary Machine Learning Postdoc jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Temporary Machine Learning Postdoc jobs in Washington, DC look for? The top searched job categories for Temporary Machine Learning Postdoc jobs in Washington, DC are:
Postdoctoral Fellow (PREP0004155)

Postdoctoral Fellow (PREP0004155)

Johns Hopkins University

Gaithersburg, MD • On-site

$53K - $72K/yr

Full-time

Posted 23 days ago


Johns Hopkins Medicine rating

7.5

Company rating: 7.5 out of 10

Based on 200 frontline employees who took The Breakroom Quiz

223rd of 870 rated healthcare providers


Job description

Description
PREP Research Associate
This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires that such institutions must be the recipient of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.
Research Title:
AI Researcher: Engineering Biology
The work will entail:
Plan and conduct research to advance measurement capabilities to aid in the predictive engineering of biological systems, such as proteins, as part of the NIST Engineering Biology Program. Develop artificial intelligence and machine learning analysis pipelines to support automation and protocol development for wetlab procedures, as well as development of platforms for new, quantitative measurements and validated methods for evaluating the functional performance of engineered biological parts and systems. Develop automation workflows for bottleneck processes in biosecurity screening and synthetic biology. Support NIST's mission through service as a subject matter expert in the application of artificial intelligence and machine learning to measurement innovation in synthetic biology. Engage stakeholders and identify opportunities for standards development.
US Citizen Preferred
Key responsibilities will include but are not limited to:
• Perform measurement analysis using artificial intelligence and/or machine learning
• Generate and maintain analysis software, along with documentation
• Conduct analysis and assist staff in conducting analysis
• Maintain and administer hardware solutions for project and group compute tasks
• Advise Division and NIST management as a subject matter expert
• Organize, conduct, and attend relevant meetings, and provide written summaries or other documentation to NIST management and stakeholders
• Obtain and provide relevant information to inform NIST management and stakeholders
• Maintain deep technical knowledge of advances in the application of artificial intelligence and machine learning to measurement challenges in synthetic biology, such as those relevant to biosafety and biosecurity
• Demonstrate attention to detail
• Execute novel technical research
• Support sequence to function research for protein engineering
• Develop and apply infrastructure for data analysis
• Establish and document standard operating procedures for analysis pipelines
Qualifications
• A Ph.D. in Computer Science, Engineering, Manufacturing, or a related field.
• 2 years of relevant experience.
• Familiarity with DevOps and CICD pipelines.
• Ability to work with real-time event data at scale.
• Familiarity with multiple scripting languages.
• Ability to develop prototypes of tools needed to analyze data.
• Strong oral and written communication skills.
Application Instructions
Please upload the following with your application:
• CV/Resume
*Please limit C.V to 3 pages only and ONLY include a valid email address for your contact info. Your resume will not be considered if the following information is included on your CV/resume.
Self portraits
Phone number
Home address/Country
Citizenship status
Languages spoken
Sex/Gender
Privacy Act Statement
Authority: 15 U.S.C. § 278g-1(e)(1) and (e)(3) and 15 U.S.C. § 272(b) and (c)
Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor's degree holders, graduate students, master's degree holders, postdocs, and faculty.
PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate administrative functions of the PREP Program.
Routine Uses: NIST will use the information collected to perform the requisite reviews of the applications to determine eligibility, and to meet programmatic requirements. Disclosure of this information is also subject to all the published routine uses as identified in the Privacy Act System of Records Notices: NIST-1: NIST Associates.
Disclosure: Furnishing this information is voluntary. When you submit the form, you are indicating your voluntary consent for NIST to use of the information you submit for the purpose stated.

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