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Job Description Summary
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Organization's Summary Statement: Dr. Kate Tully’s Agroecology Lab at the University of Maryland is seeking an Associate Research Scientist with extensive experience in the domains of decision support tools, cover crops, and sustainable agriculture. This position is housed in a lab that explores the interface of agriculture and ecology, where fields, farms, and landscapes promote crop productivity, ecosystem services, and livelihoods. We encourage candidates from a range of agricultural systems backgrounds to apply. Please note that this position is not available for visa sponsorship.
Duties and Responsibilities: The incumbent Associate Research Scientist must be willing and able to take the lead in writing grant proposals to maintain continued financial support for their position, in addition to the following expectations:
- Serve as Program Manager for the Northeast Cover Crops Council, providing support to the governing board by scheduling and conducting monthly meetings, maintaining written documentation of council activities, managing the council website (https://northeastcovercrops.com/), liaising with counterparts in the other regional cover crops councils and stakeholders, and developing/assisting in the development of council activities and products.
- Update and expand the scope of the data in the cover crop species selector and seeding rate calculator decision support tools (https://www.precisionsustainableag.org/decision\-support\-tools) developed by the cover crop councils in collaboration with the Precision Sustainable Agriculture network; expand tool utility.
- Conduct outreach and training on the Precision Sustainable Agriculture cover crop decision support tools.
- Collaborate with the Agroecology Lab and other members of the Dept. of Plant Science \& Landscape Architecture to generate grant proposals.
- Collaborate with scientists and graduate students in the Agroecology Lab to participate in ongoing projects as needed.
- Support the training of graduate students in science\-based skills such as the development and presentation of research reports.
- Prepare peer\-reviewed manuscripts and technical reports based on outreach and tool development activities.
Physical Demands:
Preferences: A Ph.D. in Agronomy, Crop and Soil Science, or a related field with a strong emphasis on cover crops, sustainability, and decision support tools is required. Candidates must have:
- A research background in crop and soil sciences and/or agronomy.
- Proficiency providing organizational support within a laboratory setting with regard to record keeping, grant management (to include writing proposals and reports), and the generation of manuscripts (to include drafting and editing documents).
- Experience with all processes involved in the development of decision support tools for sustainable agricultural practices, with an emphasis on locating, collating, and populating data; conducting quality control on data; and performing tool user testing.
- Proficiency in data collaboration and communication tools (e.g., Airtable).
- A minimum of five years in an Assistant Research Scientist\-type role.
- A minimum of ten years working across institutional and state lines with stakeholder\-focused organizations to conduct research, create outreach products, and organize outreach activities/adult education opportunities such as train the trainer events targeted to both layman and scientific audiences.
Preferred Qualifications:
- Experience with sustainable agriculture techniques, particularly in row crop systems.
- Familiarity with mid\-Atlantic and Northeastern US agricultural systems.
- Demonstrated publication record in relevant areas.
- Experience working across US regions to conduct research, create outreach products, and organize outreach activities/adult education opportunities such as train the trainer events targeted to both layman and scientific audiences.
Licenses/ Certifications:
Additional Job Details
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Minimum Qualifications: A Ph.D. in Agronomy, Crop and Soil Science, or a related field with a strong emphasis on cover crops, sustainability, and decision support tools is required. Candidates must have:
A research background in crop and soil sciences and/or agronomy.
Proficiency providing organizational support within a laboratory setting with regard to record keeping, grant management (to include writing proposals and reports), and the generation of manuscripts (to include drafting and editing documents).
Experience with all processes involved in the development of decision support tools for sustainable agricultural practices, with an emphasis on locating, collating, and populating data; conducting quality control on data; and performing tool user testing.
Proficiency in data collaboration and communication tools (e.g., Airtable).
A minimum of five years in an Assistant Research Scientist\-type role.
A minimum of ten years working across institutional and state lines with stakeholder\-focused organizations to conduct research, create outreach products, and organize outreach activities/adult education opportunities such as train the trainer events targeted to both layman and scientific audiences.
Preferred Qualifications:
Experience with sustainable agriculture techniques, particularly in row crop systems.
Familiarity with mid\-Atlantic and Northeastern US agricultural systems.
Demonstrated publication record in relevant areas.
Experience working across US regions to conduct research, create outreach products, and organize outreach activities/adult education opportunities such as train the trainer events targeted to both layman and scientific audiences.
Required Application Materials: Cover letter highlighting relevant experience and research interests, CV, contact information for 3 references
Best Consideration Date: 8/24/2026
Posting Close Date: 9/01/2026
Open Until Filled: YES
Financial Disclosure Required
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For more information on Financial Disclosure, please visit Maryland's State Ethics Commission website .
Department
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AGNR\-Plant Science \& Landscape Architecture
Worker Sub\-Type
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Faculty Regular
Salary Range
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$80,000\-$99,000
Benefits Summary
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For more information on Regular Faculty benefits, select this link .
Background Checks
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Offers of employment are contingent on completion of a background check. Information reported by the background check will not automatically disqualify anyone from employment. Before any adverse decision, the finalist will have an opportunity to provide information to the University regarding disclosable background check information. The University reserves the right to rescind the offer of employment or otherwise decline or terminate employment if the information reported by the background check is deemed incompatible with the position, regardless of when the background check is completed.
Employment Eligibility
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The successful candidate must complete employment eligibility verification (on Form I\-9\) by presenting documents that establish identity and work authorization within the timeframe required by federal immigration law, and where applicable, to demonstrate renewed employment authorization. Failure to complete employment eligibility verification or reverification within the timeframe set forth by law may result in suspension or termination of employment.
EEO Statement
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The University of Maryland, College Park is an Equal Opportunity Employer. All qualified applicants will receive equal consideration for employment. Please read the University’s Equal Employment Opportunity Statement of Policy.
Title IX Non\-Discrimination Notice
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Salary Context
This $80K-$99K range is in the lower quartile for Research Scientist roles in our dataset (median: $195K across 149 roles with salary data).
Role Details
About This Role
Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.
The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.
Across the 4,317 AI roles we're tracking, Research Scientist positions make up 4% of the market. At University of Maryland University College, this role fits into their broader AI and engineering organization.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
What the Work Looks Like
A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
Skills in Demand for This Role
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.
Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
Compensation Benchmarks
Research Scientist roles pay a median of $222,200 based on 378 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $110,000. This role's midpoint ($89K) sits 60% below the category median. Disclosed range: $80K to $99K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
University of Maryland University College AI Hiring
University of Maryland University College has 1 open AI role right now. They're hiring across Research Scientist. Based in College Park, MD, US. Compensation range: $99K - $99K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.
From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.
The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.
What to Expect in Interviews
Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.
When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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