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GRUNUSS

Partnerships

v1.0 · 2026

Inside the
open scientific
tradition.

Academic partnerships extend the institution's methodological reach and hold its outputs to external standards of validation. Collaborations are programmatic, reciprocal, and long-horizon.

§ 01 / Premise

GS-2026 / SECT_01

Compatibility precedes capability.

Partnerships are selected for compatibility with stewardship, institutional maturity, and long-horizon intent. Capability without compatibility is a structural risk, not an opportunity. Misalignment on any single dimension of the filter below is sufficient to defer or decline — clarity of refusal is treated as part of clarity of identity.

§ 02 / Types

GS-2026 / SECT_02

Bridging method and matter.

Grunuss operates as an institution that bridges the gap between academic science and industrial practice. Partnerships fall into two structurally distinct types — each carrying a different share of the same long-horizon program.

TP.01

Academic partnerships

Methodology, validation, formation.

Universities and research institutes extend the scientific reach of the institution — solver development, electronic-structure validation, doctoral pathways, and the open scientific tradition under which results are interpreted.

TP.02

Industrial partnerships

Application, fabrication, deployment.

Industrial partners carry methods into manufacturable form — precision processes, in-process metrology, materials engineering, and the operational discipline required for predictions to meet observed behaviour at scale.

§ 03 / Alignment Filter

GS-2026 / SECT_03

Three dimensions must align before any engagement.

Every prospective partnership is evaluated against the three dimensions below. Misalignment on any single dimension is sufficient to defer or decline. The filter applies equally to academic collaborations, industrial engagements, capital partnerships, and institutional advisory relationships.

AF.01
Ethical compatibilityCommitment to responsible technological development.
The partner's operating posture must reflect avoidance of extraction logic, recognition of stewardship as a structural commitment, and capacity to hold the long-horizon implications of joint work.
AF.02
Technical integrityDemonstrated seriousness in engineering and science.
Engineering rigor, scientific transparency, and intellectual honesty are required as institutional behaviour — not as marketing posture. Evidence comes from prior work, not from prior claims.
AF.03
Strategic coherenceAlignment between stated objectives and operational behaviour.
What the partner says about its mission must match how it actually operates. Divergence between declared posture and demonstrated behaviour is treated as a structural warning, not a presentational accident.

§ 04 / Stages

GS-2026 / SECT_04

From research to deployment.

Partnerships unfold across four sequential stages. The first two are conducted with academic partners; the last two with industrial partners. Together they form the bridge by which scientific method is carried into manufactured matter.

  1. ST.01 · Stage 01

    ACA

    Foundational research

    Theoretical foundations, solver development, and quantum-informed simulation methods established with academic partners.

  2. ST.02 · Stage 02

    ACA

    Methodological validation

    Electronic-structure validation, material characterisation, and doctoral pathways that hold methods to external scientific standards.

  3. ST.03 · Stage 03

    IND

    Process transfer

    Translation of validated methods into manufacturable processes — precision additive manufacturing and materials engineering with industrial partners.

  4. ST.04 · Stage 04

    IND

    Deployment & qualification

    In-process metrology, observed-vs-predicted closure under operating conditions, and qualification of functional structures at scale.

§ 05 / Principles

GS-2026 / SECT_05

How partnerships are conducted.

PP.01
Scientific independence
Partnerships do not constrain publication, methodology, or interpretation of results.
PP.02
Reciprocal contribution
Each engagement defines shared inputs, shared outputs, and shared accountability for findings.
PP.03
Long-horizon alignment
Partners selected for sustained programmatic fit rather than one-off project convenience.
PP.04
Open scientific tradition
Joint outputs are published with full methodology, constraints, and uncertainty bounds.
PP.05
Operational discipline
Transfer to industrial partners is governed by manufacturability envelopes, in-process metrology, and the requirement that predictions meet observed behaviour at scale.

§ 06 / Modes

GS-2026 / SECT_06

Modes of collaboration.

Modes of partner collaboration.
CodeTypeModeDetail
MD.01ACAJoint research programsMulti-year programs with shared scientific objectives and co-authored outputs across Grunuss and partner institutions.
MD.02ACADoctoral pathwaysStructured pathways for doctoral researchers to work across Grunuss and partner institutions, with formation held to external scientific standards.
MD.03ACAIn-process metrologyIn-process measurement of functional structures during fabrication, used to bound predictions against observed behaviour at scale.
MD.04INDPilot fabricationPrecision additive manufacturing of functional structures with industrial partners, within defined processability envelopes.
MD.05INDProcess transferTranslation of validated methods into manufacturable processes — materials engineering and qualification of functional structures at industrial scale.
MD.06INDInstrumented validationAccess to partner-side characterisation infrastructure for observed-vs-predicted closure under operating conditions.

§ 07 / Academic

GS-2026 / SECT_07

Current academic partners.

PT.01

University of Cordoba

Spain

Focus

Numerical simulation of complex physical systems.

PT.02

Uppsala University

Sweden

Focus

Advanced material characterisation and electronic-structure validation.

PT.03

Cracow Institute of Technology

Poland

Focus

AI-assisted, quantum-informed simulation.

PT.04

VŠB – Technical University of Ostrava

Czech Republic

Focus

Mathematical and theoretical foundations of AI.

[Additional partners will be added as agreements are formalised.]