Startup Appendices

Appendix A: Faculty Research Startup Package Allocation Rubric

Kansas State University | Office of the Vice President for Research
Effective July 1, 2026

Executive Summary

This rubric provides a systematic, equitable framework for allocating research startup packages to new tenure-track faculty hires across all colleges and disciplines. The framework accounts for tenure status, academic rank, years of prior research experience, grantsmanship track record, research field, and institutional alignment. Startup packages are designed to be allocated over 3 years and enable new faculty to establish competitive research programs, generate preliminary data for external funding, and achieve scholarly productivity within the first 3-5 years of appointment.

Key Principle:

Startup funding is a time-limited (3-year) investment in research initiation, with the expectation that external funding and ongoing university investments in faculty salaries and laboratory space will sustain research beyond the startup period.

I. Eligibility and Baseline Requirements

Eligibility and baseline requirements are defined in the Policy on New Faculty Research Startup Funding: Process and Allocation (Section I).

II. Funding Level Calculation

A. Base Tier Structure

Startup packages are calculated through a two-step process.

  1. Base allocation by academic rank: Establishes the initial funding level.
  2. Multi-factor scoring model: Adjusts the allocation based on candidate and research-specific factors, up to the approved maximum threshold.

Scoring dimensions:

  • Academic Rank & Tenure Status (Base Allocation)
  • Years of Prior Research Experience (Adjustment Factor)
  • Prior Grantsmanship & Funding Track Record (Multiplier)
  • Research Field & Infrastructure Needs (Field-Specific Scaling)
  • Strategic Institutional Fit (Modifier)
  • Research Effort (FTE) Adjustment

B. Base Allocation and Maximum Startup by Rank

Base Allocation represents the standard starting level for funding determination. Final awards may be adjusted upward or downward using the multi-factor model, but may not exceed the maximum startup threshold. Humanities, Arts, and Design allocations are fixed at $10,000 and cannot be adjusted without authorization from the Vice President for Research.

TIER 1: Assistant Professor

Category S/T/E/V Fields Applied Agricultural Sciences Non-STEV/Social Sciences Humanities, Arts, and Design
Base Allocation $250,000-350,000 $200,000-300,000 $75,000-$100,000 $10,000
Maximum Startup $600,000 $400,000 $150,000 $10,000
Typical 3-Yr Allocation* $300,000-500,000 $250,000-350,000 $100,000-125,000 $10,000

*Typical totals reflect adjusted allocations following application of the multi-factor scoring model.

Notes:
    • S/T/E/V includes life sciences, physical sciences, veterinary medicine, computer science, and all engineering disciplines.
    • Applied Agricultural Sciences includes animal science, plant science, and food science.

TIER 2: Associate/Full Professor (Endowed Chair or Major Recruitment)

Category S/T/E/V Fields Applied Agricultural Sciences Non-STEV/Social Sciences Humanities, Arts, and Design
Base Allocation $200,000-300,000 $180,000-280,000 $75,000-$125,000 $10,000
Maximum Startup $800,000 $500,000 $200,000 $10,000
Typical 3-Yr Allocation* $300,000-500,000 $250,000-400,000 $100,000-150,000 $10,000

*Typical totals reflect adjusted allocations following application of the multi-factor scoring model.

Note:
    • Full professors are rare startup candidates unless these are targeted recruitments to address a strategic institutional research need. Allocations reflect senior-level research expectations.

III. Adjustment Factors and Multipliers

Final startup allocations are adjusted from the base allocation using a multi-factor scoring model. Adjustments may increase or decrease the base allocation, but final awards may not exceed the maximum startup threshold.

A. Years of Prior Research Experience

Score the candidate's post-degree research experience, including postdoctoral, graduate, and prior faculty roles, to determine an experience-based multiplier:

Experience Level Years Multiplier Justification
Early Career 0-3 years x 0.8 Limited track record; lower startup allocation
Developing Career 4-7 years x 1.0 Standard baseline; typical for a new assistant professor hire
Established Early Career 13-20 years x 1.2 Proven capability; may bring existing funding
Mid Career 13-20 years x 1.3-1.5 Senior associate professor trajectory; established externally funded program
Distinguished Career 20+ years x 1.5-2.0 Full professor hire; significant research leadership and infrastructure demands

Examples:

  • PhD 2020, postdoc 2021–2023, Assistant Professor hire 2024 → 4 years experience →0× multiplier
  • PhD 2015, postdoc 2016–2018, faculty 2018–2024, now seeking new position → 9 years →2× multiplier

B. Prior Grantsmanship and Funding Success Track Record

Funding Track Record Criteria Score Multiplier
No Prior External Funding No grants as PI or Co-I; research conducted on mentor funding 1 x 0.7-0.9
Limited Funding
(<$500K total)		 1-2 small grants; limited competitive success; mostly departmental support 2 x 0.9-1.0
Moderate Funding
($500K-2M)		 Multiple grants; NSF or similar agency; 40-60% success rate 3 x 1.0-1.2
Strong Funding
($2M-5M)		 NIH R01s, USDA, NSF CAREER or equivalent; proven grantsmanship; 50% success rate 4 x 1.2-1.4
Excellent Funding
(>$5M)		 Multiple R01s or equivalent; leadership on large multi-institutional projects; 60%+ success rate 5 x 1.4-1.6

Special Considerations:

  • USDA-ARS funding experience is considered equivalent to NIH/NSF funding.
  • Externally sponsored research at land-grant institutions, including support from industry and commodity organizations, is recognized if outcomes are published through external, peer-reviewed outlets.
  • Extension research and other forms of scholarly dissemination are valued in assessing grantsmanship.

C. Research Field and Infrastructure Scaling Factor

Determine typical infrastructure and resource requirements associated with the candidate’s research field. Classification should reflect the primary research methodology and core infrastructure needs required to initiate the research, rather than occasional, future, or high-cost outlier activities.

Research Field Infrastructure
Intensity		 Scaling
Factor		 Notes
S/T/E/V — Experimental Biology/Life Sciences and Veterinary Medicine Very High x 1.3-1.5 Equipment, reagents, live organism housing, safety protocols
Animal Science High x 1.1-1.3 Animal care (labor-intensive), facilities, regulatory compliance, welfare monitoring
Agricultural Field Research High x 1.1-1.3 Land access, field equipment, seasonal personnel, long-term trials
Food Science — Lab-based High x 1.1-1.3 Lab equipment, food processing facilities, microbiome/food safety studies
Food Science — Applied/facility-based Low-Moderate x 0.8-1.0 Shelf-life testing, dairy production work
Engineering — Experimental/materials Very High x 1.3-1.5 Instrumentation, fabrication equipment, testing apparatus
Computer Science/Informatics Low-Moderate x 0.8-1.0 Computing resources, software licenses, and limited physical equipment
Chemistry/Physics High x 1.1-1.3 Specialized instrumentation, high equipment costs, safety equipment
Geosciences High x 1.1-1.3 Field equipment, sample analysis, travel to collection sites
Social Sciences/Economics Low-Moderate x 0.8-1.0 Survey tools, data management, limited equipment; primarily personnel
Public Health Moderate-High x 1.0-1.2 Depending on the method (community-based lower, lab-based higher)

D. Strategic Institutional Fit and Alignment Modifier

Fit Level Criteria Modifier
Misaligned Hire does not align with institutional research priorities; limited collaboration potential; primarily addresses staffing gaps x. 085-0.95
Neutral Standard hire; meets departmental needs; some alignment with existing centers/institutes x 1.0
Well Aligned Supports university research clusters, interdisciplinary centers, or strategic initiatives; demonstrated collaboration partnerships x 1.05-1.15
Highly Strategic Addresses emerging institutional priority; anticipated high external visibility; leadership potential in center/institute; likely to generate significant future grants x 1.15-1.30

Examples of Strategic Priority (adjusted annually):

  • Agriculture, food security, and Food for Health (Food is Medicine)
  • Environmental sustainability and climate adaptation
  • Animal health and welfare innovation
  • Precision agriculture and agricultural technology
  • Advanced nuclear reactor research and secure energy
  • Biomanufacturing and biotechnology
  • Enabling technologies and Artificial Intelligence (AI) Research
  • Interdisciplinary research clusters

E. Research Effort (FTE) Adjustment

Allocations are scaled proportionally based on the faculty member’s assigned research effort.

Research Effort Adjustment = (Research FTE x 2)

Examples:

  • 2 FTE = 0.4×
  • 5 FTE = 1.0×
  • 7 FTE = 1.4×
Note:

Research effort adjustments apply to the overall startup allocation

IV. Calculation Model and Examples

A. Calculation Formula

The startup package is calculated by applying all adjustment factors and modifiers to the base allocation:

Startup Package = (Base allowcation by rank & field) x (Experience muliplier) x (Grantsmanship multiplier) x (infrastructure scaling) x (Strategic modifier) x (Research effor adjustment)

Policy Limits:

  • No allocation may exceed the maximum startup threshold for the candidate’s rank and field.
  • Humanities, Arts, and Design allocations remain fixed at $10,000 and cannot be adjusted.

B. Worked Examples

Example 1: Assistant professor, animal science (strong grantsmanship)

  • Base Allocation (Assistant Professor, Applied Agricultural Sciences): $200,000–$300,000 → Select $250,000 (midpoint)
  • Years of Experience: 6 years (postdoc 2 yrs, prior faculty 4 yrs) →0× multiplier
  • Prior Grantsmanship: 2 USDA grants, 1 NSF grant (~$2.3M total), 60% success rate →3× multiplier
  • Infrastructure: Animal Science (High) →3× scaling
  • Strategic Fit: Strong alignment with university animal welfare initiative →20× modifier
  • Research Effort: 0.40 FTE × 2= 0.8×

Calculation: $250,000 × 1.0 × 1.3 × 1.3 × 1.2 × 0.8 = $405,600 (capped at $400,000 for tier; excess can be requested as non-startup research support)

Recommended Allocation: $400,000

Breakdown of Use (itemized during negotiation):

  • Graduate student support (2.5 years, 2 students × $35K/year): $175,000
  • Equipment (animal monitoring, welfare assessment tools): $60,000
  • Summer salary support (3 summers, $30K/year): $90,000
  • Lab operations & supplies: $40,000
  • Conference travel & publication: $15,000
  • Graduate student tuition & benefits (if not covered): $20,000

Example 2: Assistant professor, computer sciences (early career)

  • Base Allocation (Assistant Professor, S/T/E/V): $250,000–$350,000 → Select $275,000 (lower end due to early career)
  • Years of Experience: 2 years postdoctoral (post-2023 PhD) →8× multiplier
  • Prior Grantsmanship: No prior external funding as PI; co-author on mentor's grant →8× multiplier
  • Infrastructure: Computer hardware and software (Low–Moderate) →9× scaling
  • Strategic Fit: Neutral, fills faculty gap but not strategic priority →0× modifier
  • Research Effort: 0.60 FTE × 2 = 1.2×

Calculation: $275,000 × 0.8 × 0.8 × 0.9 × 1.0 × 1.2 = $190,080

Recommended Allocation: $195,000

Breakdown of Use:

  • Computing infrastructure & hardware: $72,500
  • Graduate student support (2.5 years, 1 student × $30K/year): $75,000
  • Summer salary (modest, 2 years × $15K): $30,000
  • Conference travel & publication: $12,500
  • Contingency/flexible research: $5,000

Example 3: Assistant professor, life sciences (developing career)

  • Base Allocation (Assistant Professor, S/T/E/V): $250,000–$350,000 → Select $350,000
  • Years of Experience: 7 years total (postdoc 3 yrs, faculty 4 yrs) →0× multiplier
  • Prior Grantsmanship: $750K in prior Federal grants, 45% success rate →05× multiplier
  • Infrastructure: S/T/E/V (Very High) Animal care (labor-intensive), containment facilities, regulatory compliance, welfare monitoring, →4× scaling
  • Strategic Fit: High alignment with university research initiatives →15× modifier
  • Research Effort: 0.50 FTE × 2 = 1.0×

Calculation: $350,000 × 1.0 × 1.05 × 1.4 × 1.15 × 1.0 = $591,675

Recommended Allocation: $595,000

V. Eligible and Ineligible Startup Expenditure Categories

Eligible and ineligible expenses are defined in Policy on New Faculty Research Startup Funding: Process and Allocation (Section VI.C).

VI. Implementation Guidelines for Departments and Deans

Procedures for startup development and approval are outlined in the Policy on New Faculty Research Startup Funding: Process and Allocation (Section IV).

VII. Appeals and Exceptions

Exceptions to rubric-calculated allocations and appeals must follow the process outlined in the Policy on New Faculty Research Startup Funding: Process and Allocation (Section II,D). Approved adjustments remain subject to the maximum thresholds defined in this rubric.

VIII. References and Recommended Reading

IX. Conclusion and Institutional Commitment

This rubric reflects Kansas State University's commitment to equity in research startup funding while recognizing the distinct infrastructure and personnel needs of different disciplines. The framework is designed to be:

  • Transparent: Clear calculation methodology and published expectations
  • Equitable: Consistent treatment within disciplines; justified adjustments for experience and track record
  • Flexible: Accommodation for interdisciplinary, cluster, and strategic initiatives
  • Accountable: Documentation, performance benchmarks, and regular reporting

Implementation Success depends on:

  1. Implementation of the hiring plan and agreement between the department head, Dean, and OVPR on the start-up package expectations and range prior to recruitment.
  2. Clear communication of agreed-upon range, expectations, and guidelines during recruitment.
  3. Collaborative negotiation between the candidate, department, college, and the OVPR.
  4. Annual monitoring, budget accountability, and realistic performance assessment.
  5. Institutional commitment to multi-year funding periods.
  6. Proactive support for transition to external funding.

Revision Schedule:

This rubric should be reviewed annually and substantially updated every three years to reflect changes in funding landscapes, disciplinary costs, and institutional priorities.

Appendix B: Startup Funding Process Flowchart