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Weekend Machine Learning Postdoc Jobs in Virginia

Williammary

Research Scientist

Gloucester Point, VA

$65K/yr

Experience integrating AI or machine learning approaches into environmental modeling * Experience ... Work closely with graduate students, postdoctoral associates, and visiting scientists * Participate ...

KOSMO MACHINE INC.

CNC Machinist

Sandston, VA

$21 - $38/hr

... Machine, precision isn't just what we do - it's who we are. As a premier, climate-controlled ... Why You'll Love Working With Us * 3 Day Weekend: Monday-Thursday, 6:00 am-4:30 pm. No mandatory ...

KOSMO MACHINE INC.

CNC Machinist

Sandston, VA

$43K - $79K/yr

... Machine, precision isn't just what we do - it's who we are. As a premier, climate-controlled ... Why You'll Love Working With Us * 3 Day Weekend: Monday-Thursday, 6:00 am-4:30 pm. No mandatory ...

Amazon

Data Scientist, AWS Security

Arlington, VA · On-site

Your expertise in statistical analysis, machine learning, and big data processing will be crucial ... We don't like getting paged in the middle of the night or on the weekend, so we work to ensure that ...

Amazon

Data Scientist, AWS Security

Arlington, VA

As a Data Scientist on our team, you will leverage advanced analytics and machine learning to ... We don't like getting paged in the middle of the night or on the weekend, so we work to ensure that ...

Amazon

Data Scientist, AWS Security

Arlington, VA · On-site

As a Data Scientist on our team, you will leverage advanced analytics and machine learning to ... We don't like getting paged in the middle of the night or on the weekend, so we work to ensure that ...

GeoDelphi

Software Engineer

Alexandria, VA · Remote

In addition, there may be occasional weekend work required. The candidate MUST be a US citizen and ... Develop and implement statistical models, machine learning workflows, and geospatial analytics ...

GeoDelphi

Software Engineer

Alexandria, VA · Remote

In addition, there may be occasional weekend work required. The candidate MUST be a US citizen and ... Develop and implement statistical models, machine learning workflows, and geospatial analytics ...

GeoDelphi

In addition, there may be occasional weekend work required. The candidate MUST be a US citizen and ... Develop and implement statistical models, machine learning workflows, and geospatial analytics ...

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Weekend Machine Learning Postdoc information

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

AspectWeekend Machine Learning PostdocWeekend Data Scientist
Required CredentialsPhD in Computer Science, Machine Learning, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field
Work EnvironmentAcademic research settings, universities, research labsIndustry companies, startups, consulting firms
Employer & Industry UsageResearch institutions, universities, academic grantsTech companies, finance, healthcare, retail
Common Search & ComparisonYesYes

The Weekend Machine Learning Postdoc typically involves academic research with a focus on advancing machine learning theories and models, often requiring a PhD. In contrast, a Weekend Data Scientist applies data analysis and machine learning techniques in industry settings, often with a bachelor's or master's degree. Both roles may work on similar projects but differ mainly in their environment, credentials, and end goals.

What are the typical projects and collaboration opportunities for a Weekend Machine Learning Postdoc?

As a Weekend Machine Learning Postdoc, you will often contribute to ongoing research projects, developing and refining machine learning models in collaboration with faculty, graduate students, and occasionally industry partners. While your hours are concentrated on weekends, you’ll typically participate in regular research meetings, code reviews, and may co-author papers or grant proposals. The role provides opportunities to mentor junior researchers and expand your expertise by working on interdisciplinary teams. This structure allows you to make significant research contributions while maintaining flexibility in your schedule.

What is a Weekend Machine Learning Postdoc?

A Weekend Machine Learning Postdoc is a postdoctoral researcher who focuses on machine learning projects and typically works on weekends or has a flexible schedule that includes weekend hours. This role often involves conducting advanced research in machine learning, developing algorithms, publishing papers, and collaborating with academic or industry teams. Weekend postdoc positions may be ideal for those balancing other commitments or seeking non-traditional work hours while continuing their research careers.

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

To thrive as a Weekend Machine Learning Postdoc, you need a strong background in machine learning, statistics, and programming, typically supported by a PhD in a relevant field. Experience with tools such as Python, TensorFlow, PyTorch, and data analysis platforms, as well as familiarity with academic research methodologies, is essential. Exceptional problem-solving abilities, self-motivation, and effective communication are vital soft skills for success in research and collaboration. These skills enable you to drive innovative research, efficiently manage independent projects, and contribute meaningful insights to the field.
What are the most commonly searched types of Machine Learning Postdoc jobs in Virginia? The most popular types of Machine Learning Postdoc jobs in Virginia are:
What are popular job titles related to Weekend Machine Learning Postdoc jobs in Virginia? For Weekend Machine Learning Postdoc jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Weekend Machine Learning Postdoc jobs in Virginia look for? The top searched job categories for Weekend Machine Learning Postdoc jobs in Virginia are:
What cities in Virginia are hiring for Weekend Machine Learning Postdoc jobs? Cities in Virginia with the most Weekend Machine Learning Postdoc job openings:
Weekend Machine Learning Postdoc jobs near you
Ecologist (Postdoctoral Research Fellow), IS-0408-09

Ecologist (Postdoctoral Research Fellow), IS-0408-09

Smithsonian Institution

Front Royal, VA • On-site

$45K - $61K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

This job post has expired 1 day ago. Applications are no longer accepted.

Smithsonian Institution rating

8.6

Company rating: 8.6 out of 10

Based on 23 frontline employees who took The Breakroom Quiz

1st of 27 rated museums

Job description

OPEN DATE: May 27, 2026          
CLOSING DATE: June 10, 2026
POSITION TYPE: Trust Fund
APPOINTMENT TYPE: Temporary Not to Exceed Twelve (12) Months (may be extended based on funds availability)
SCHEDULE: Full Time
DUTY LOCATION: Hillsborough, NJ
Position sensitivity and risk:
Non-sensitive (NS)/Low Risk
Who May Apply:
Open to all Qualified Applicants
What are Trust Fund Positions?
Trust Fund positions are unique to the Smithsonian. They are paid for from a variety of sources, including the Smithsonian endowment, revenue from our business activities, donations, grants and contracts. Trust employees are not part of the civil service, nor does trust fund employment lead to Federal status. The salary ranges for trust positions are generally the same as for federal positions and in many cases trust and federal employees work side by side. Trust employees have their own benefit program and may include Health, Dental & Vision Insurance, Life Insurance, Transit/Commuter Benefits, Accidental Death and Dismemberment Insurance, Annual and Sick Leave, Family Friendly Leave, 403b Retirement Plan, Discounts for Smithsonian Memberships, Museum Stores and Restaurants, Credit Union, Smithsonian Early Enrichment Center (Child Care), Flexible Spending Account (Health & Dependent Care). 
 
Conditions of Employment
  • Pass Pre-employment Background Check and Subsequent Background Investigation for position designated as low risk.
  • Complete a Probationary Period
  • Maintain a Bank Account for Direct Deposit/Electronic Transfer.
  • The position is open to all candidates eligible to work in the United States.  Proof of eligibility to work in U.S. is not required to apply.
  • Applicants must meet all qualification and eligibility requirements within 30 days of the closing date of this announcement. 
IINTRODUCTION
The Smithsonian Institution is the world's largest museum, education, and research complex, with 21 museums and the National Zoo. This position is located in the Smithsonian's National Zoo and Conservation Biology Institute (NZCBI), Washington, DC. NZCBI plays a leading role in the Smithsonian's global efforts to save wildlife species from extinction and train future generations of conservationists.

Duke Farms is a center of the Doris Duke Foundation. It is a 2,700-acre living laboratory in New Jersey where restoration, research, and public engagement converge to test and scale real-world conservation solutions. The Center for Conservation at Duke Farms builds on this foundation as a national platform that integrates long-term socio-ecological research with applied science, training, and decision-support tools. The Center's mission is to close the gap between science and implementation, generating evidence, validating it in practice, and equipping partners to deploy it at scale. 

SUMMARY
The Smithsonian's National Zoo & Conservation Biology Institute is seeking a postdoctoral researcher to lead the development of next-generation landscape connectivity science, advancing state-of-the-art modeling approaches that integrate high-resolution remote sensing, machine learning, and circuit- and network-based methods. The postdoc will build reproducible, open-source modeling pipelines and decision-support tools, designed for platforms such as Google Earth Engine, that allow for scenario testing, continuous updating, and direct application in planning and policy contexts. This work will bridge cutting-edge analytics with real-world implementation, producing scalable tools that standardize methods across jurisdictions and enable practitioners to identify, prioritize, and operationalize connectivity solutions for biodiversity and climate resilience. 
LOCATION
Center for Conservation, Duke Farms, Hillsborough, NJ
The post-doctoral fellow will use available environmental and biodiversity data, demonstrating significant programming and analytical skills, to integrate remote sensing data layers to forecast how land use/land cover change, human impacts, resource availability, and projected climate change are predicted to impact structural and functional connectivity across New Jersey and beyond.  He/she will create an ecological framework for analyses that can be replicated across other states throughout the region. The post-doctoral fellow will be encouraged and expected to develop their own research objectives that fit in with the project. 

Serves as a consultant and advisor on professional matters in their area of expertise to colleagues, Federal agencies, institutions, organizations, and the general public. May assist with guidance and teaching of students and technicians working on one or more research projects. May train staff members, interns, fellows, students, and visiting scholars in the theory and practical use of specialized equipment as appropriate. Advises researchers in the interpretation of the obtained data and ensures safe and responsible work practices with such equipment.
Assists in preparation and submission of grant proposals. Reviews research proposals, manuscripts, and publications as requested by scientific colleagues and outside institutions. Lectures to professional associations and other organizations. Attends and participates in national and international scientific conferences, seminars, and societies.

Performs other related duties as assigned.

 
Education and Experience:
A. Degree: Bachelor's degree from an accredited college or university in biology or a related field of science underlying ecological research that involved at least 30 semester hours of coursework in basic and applied biological sciences. These hours must have included at least 9 semester hours in ecology, and 12 semester hours in physical and mathematical sciences. 
OR 
B. Combination of education and experience -- at least 30 semester hours of courses equivalent to a major in any combination of biological sciences, statistics, or mathematics, with required course work as shown in A above, plus appropriate experience or additional education. 
 
Additional Requirements: 
A Ph.D. or equivalent doctoral degree that has equipped applicants with the knowledge, skills, and abilities (described below) necessary to do the work of the position.  

Willing and able to reside in New Jersey.  
SPECIALIZED EXPERIENCE 
  • Expertise and experience in advanced spatial analysis, with expertise in incorporating remote sensing variables in analytical frameworks. The applicant must demonstrate the ability to manipulate large spatial databases. 
  • Demonstrated expertise in connectivity modeling, inclusive of least-cost path and/or circuit theory frameworks (e.g., Circuitscape, Omniscape). 
  • Experience manipulating raster datasets, with a background performing supervised land-cover classifications. 
  • Demonstrated skill in analysis of R; computer programming (e.g., Python, Java, and/or Google Earth Engine) and experience working with large spatial datasets advantageous.  
  • Experience designing, organizing, and managing field work. 
  • Experience collaborating across institutions to jointly pursue research topics relevant to both academic and applied audiences. 
Applicants who wish to qualify based on education completed outside the United States must be deemed equivalent to higher education programs of U.S. Institutions by an organization that specializes in the interpretation of foreign educational credentials. This documentation is the responsibility of the applicant and should be included as part of your application package. 

HOW TO APPLY: 
CV/Resume must include a description of your paid and non-paid work experience that is related to this job; starting and ending dates of job (month and year); and average number of hours worked per week.  
CV/Resume must include the month and year of all degrees earned; professional and relevant volunteer experience; peer-reviewed publications; competitive funding received; any honors or awards received; memberships in professional societies; presentations given at national/international meetings; and names, addresses, and phone numbers of four persons familiar with your scientific stature, contributions, and recognition. Earned academic degrees must be verified with copies of official university transcripts that clearly state the classes taken, degree awarded, the major, and date of conferral. 
CV/Resume must clearly identify how you fulfill the SPECIALIZED EXPERIENCE to be considered. 
Failure to provide this information and documents will result in your application receiving no further consideration. 
A cover letter can be included with the application materials to summarize the applicant's training, experience, and interest in the position.
Any false statement in your application may result in your application being rejected and may also result in termination after employment begins.
  
Join us in "Inspiring Generations through Knowledge and Discovery."
 
What To Expect Next: Once the vacancy announcement closes, a review of your resume will be compared against the qualification and experience requirements related to this job. After review of applicant resumes is complete, qualified candidates will be referred to the hiring manager.
 
Relocation expenses are not paid.
The Smithsonian Institution provides reasonable accommodation to applicants with disabilities where appropriate. Applicants requiring reasonable accommodation should contact biagasl@si.edu. Determinations on requests for reasonable accommodation will be made on a case-by-case basis.  To learn more, please review the Smithsonian's Accommodation Procedures.
 
The Smithsonian Institution is an Equal Opportunity Employer. We believe that a workforce comprising a variety of educational, cultural, and experiential backgrounds support and enhance our daily work life and contribute to the richness of our exhibitions and programs. See Smithsonian EEO program information: www.si.edu/oeema.

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