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Temporary Evidence Synthesis Jobs (NOW HIRING)

Aquent

Event Content Strategy and Lead

San Francisco, CA · On-site

$80 - $95/hr

Temporary Salary: $80-95 Hourly Please include a portfolio with application Aquent is seeking a ... Research & Synthesis: Gather internal and external data, stories, and medical literature to support ...

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Temporary Evidence Synthesis information

What is a temporary evidence synthesis?

A Temporary Evidence Synthesis is a short-term or project-based role focused on collecting, evaluating, and summarizing research findings to inform decisions, policies, or guidelines. Individuals in this position systematically review available evidence, often for time-sensitive projects or emerging issues. They may work within academic, healthcare, or policy organizations to deliver clear and concise reports. The role requires strong analytical skills and the ability to interpret scientific studies efficiently.

What are some typical challenges faced by professionals in temporary evidence synthesis roles, and how are they addressed?

Professionals in Temporary Evidence Synthesis often face tight deadlines, rapidly changing project scopes, and the need to quickly appraise large volumes of literature. To address these challenges, teams typically use standardized protocols and systematic review tools to streamline the evidence-gathering process. Regular communication with project stakeholders and collaboration with subject matter experts are also key strategies to ensure the synthesis remains focused, relevant, and high-quality despite time constraints.

What are the key skills and qualifications needed to thrive as a temporary evidence synthesis specialist, and why are they important?

To thrive as a Temporary Evidence Synthesis Specialist, strong analytical skills, experience in literature review, and a background in fields such as public health, medicine, or social sciences are generally required. Familiarity with systematic review software (e.g., Covidence, RevMan), reference management tools, and an understanding of evidence grading frameworks like GRADE is typical. Attention to detail, strong written communication, and the ability to work independently under tight deadlines are critical soft skills. These competencies ensure the accurate, timely, and credible synthesis of research evidence to inform decision-making.

What is the difference between Temporary Evidence Synthesis vs Evidence Analyst?

AspectTemporary Evidence SynthesisEvidence Analyst
CredentialsTypically requires research or health-related certifications, often with temporary or contract experienceRequires similar research or data analysis certifications, often with ongoing professional development
Work EnvironmentUsually project-based, temporary settings within research institutions or healthcare organizationsPermanent or long-term roles within research teams, government agencies, or private firms
Industry UsageCommon in healthcare, clinical research, and policy development sectorsWidely used in research, healthcare, and data analysis industries

Temporary Evidence Synthesis professionals focus on short-term projects to compile and analyze evidence, often in healthcare or research settings. Evidence Analysts typically hold ongoing roles, analyzing data and evidence to inform decisions. While both roles require similar skills and certifications, their employment duration and project scope differ.

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What cities are hiring for Temporary Evidence Synthesis jobs?

Cities with the most Temporary Evidence Synthesis job openings:

What are the most commonly searched types of Evidence Synthesis jobs?

The most popular types of Evidence Synthesis jobs are:

What states have the most Temporary Evidence Synthesis jobs?

States with the most job openings for Temporary Evidence Synthesis jobs include:

What job categories do people searching Temporary Evidence Synthesis jobs look for?

The top searched job categories for Temporary Evidence Synthesis jobs are:

Temporary Evidence Synthesis jobs near you
Infographic showing various Temporary Evidence Synthesis job openings in the United States as of August 2026, with employment types broken down into 64% Full Time, 18% Part Time, and 18% Temporary. Highlights an 91% In-person, and 9% Remote job distribution.

Senior Software Test and Automation Engineer (R4472)

Shield AI

San Diego, CA • On-site

$110K - $170K/yr

Full-time

Re-posted 23 days ago

Job description

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

Job Description:
Shield AI's Software Test & Automation Team develops the verification, validation, and automation capabilities that enable rapid delivery of Hivemind autonomy across the Expeditionary and Emerging Operations portfolio. Our mission is to provide objective evidence of software quality, reliability, and mission readiness by building scalable automated test frameworks, repeatable validation environments, and data-driven readiness assessments spanning simulation, Software-in-the-Loop (SIL), Hardware-in-the-Loop (HIL), and Vehicle-in-the-Loop (VIL) environments. 

As a Senior Software Test & Automation Engineer, you will design and develop automated test infrastructure, execute system-level verification activities, analyze software performance, and build the tooling that enables continuous validation throughout the development lifecycle. Working closely with autonomy software, systems engineering, digital infrastructure, and flight test teams, you will help ensure autonomy capabilities are validated, repeatable, and ready for operational deployment. 

What you'll do:

  • Design, develop, and maintain automated test frameworks, validation tooling, and test infrastructure supporting autonomy software.  

  • Develop and execute verification and validation strategies across simulation, SIL, HIL, VIL, and representative system environments.  

  • Build automated regression, integration, functional, and performance test suites that improve software quality and deployment confidence.  

  • Develop Python-based automation, test harnesses, and analysis tools that reduce manual testing effort and improve repeatability.  

  • Analyze test results, identify software defects and integration issues, and support cross-functional root cause investigations.  

  • Develop software quality metrics, dashboards, and readiness assessments that provide objective evidence of software maturity.  

  • Integrate automated testing into CI/CD workflows to enable continuous validation and rapid developer feedback.  

  • Collaborate with autonomy software, systems engineering, flight test, and integration teams to define validation strategies and readiness criteria.  

  • Improve test infrastructure, automation coverage, and validation methodologies across the Expeditionary and Emerging Operations portfolio. 

Required qualifications:

  • BS in Computer Science, Aerospace, Electrical, Mechanical Engineering or related field.  

  • 4-7 years developing software test, verification, automation, or validation solutions for robotics, autonomy, aerospace, or other complex distributed systems.  

  • Strong proficiency in Python for automation, testing, and data analysis.  

  • Experience developing automated test frameworks, test harnesses, or validation infrastructure.  

  • Experience with Linux-based development environments.  

  • Experience validating software in simulation, SIL, HIL, and/or representative hardware environments.  

  • Experience debugging complex software and system integration issues.  

  • Experience with CI/CD pipelines and continuous validation practices.  

  • Strong understanding of software verification, regression testing, and quality assurance methodologies. 

Preferred qualifications:

  • Experience with flight control systems such as ArduPilot or PX4. 

  • Experience with unmanned aerial systems (fixed-wing, quadrotor, or both)  

  • Background in autonomy, robotics, or aerospace systems  

  • Familiarity with flight controllers, radios, and communications systems 

$110,000 - $170,000 a year
#LI-LD1
#LC

Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
 
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
 
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
 
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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