An applied Swiss-inspired curriculum combining algorithmic rigour, systems architecture, digital trust and practical engineering capability for modern technology leaders.
The Executive Doctorate in Robotics and Intelligent Automation at Brookfield School of Computing is engineered to provide deep competency across core computer science, systems design, and targeted domain applications. Students develop fluency in software craftsmanship, distributed architectures, algorithm optimization, and data governance.
Instruction balances rigorous theoretical foundations with practical code repositories, laboratory simulations, and ethical technology review aligned with modern international computing standards.
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| DOC101 | Philosophy of Technical Sciences & Epistemology in Robotics and Intelligent Automation | Theory | Examine computational ontology, paradigm shifts, falsificationism and scientific epistemology in Robotics and Intelligent Automation. |
| DOC102 | Doctoral Research Methodology & Design Science Research in Robotics and Intelligent Automation | Theory | Formulate Hevner's Design Science Research guidelines, rigor vs relevance cycles and doctoral artifact design in Robotics and Intelligent Automation. |
| DOC103 | Empirical Research Formulation & Quantitative Inquiry in Robotics and Intelligent Automation | Practical | Design formal empirical investigations, controlled computational experiments and statistical hypothesis test suites in Robotics and Intelligent Automation. |
| DOC104 | Theoretical Frameworks & Advanced Systems Modeling in Robotics and Intelligent Automation | Theory | Deconstruct axiomatic systems models, state transition systems and formal verification in Robotics and Intelligent Automation. |
| DOC105 | Computational Experimentation & Statistical Verification in Robotics and Intelligent Automation | Practical | Execute Monte Carlo simulations, power calculations and non-parametric statistical tests in Robotics and Intelligent Automation using R and Python. |
| DOC106 | Critical Literature Synthesis & State-of-the-Art Analysis in Robotics and Intelligent Automation | Theory | Perform systematic literature reviews (PRISMA), meta-analyses and theoretical gap identification in Robotics and Intelligent Automation. |
| DOC107 | Systems Epistemology & Architectural Thinking in Robotics and Intelligent Automation | Theory | Evaluate socio-technical systems theory, emergence in complex adaptive architectures and structural decoupling in Robotics and Intelligent Automation. |
| DOC108 | Research Ethics, Responsible Innovation & Swiss Standards in Robotics and Intelligent Automation | Practical | Audit doctoral research protocols against Swiss human research ethics, algorithmic safety and data governance in Robotics and Intelligent Automation. |
| DOC109 | Doctoral Research Scoping & Initial Proposal Portfolio in Robotics and Intelligent Automation | Theory | Author the preliminary doctoral scoping portfolio defining novel research questions, significance and scope in Robotics and Intelligent Automation. |
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| DOC201 | Advanced Doctoral Proposal Defense & Technical Roadmap in Robotics and Intelligent Automation | Theory | Defend the comprehensive doctoral research proposal, methodology and experimental roadmap in Robotics and Intelligent Automation before a faculty panel. |
| DOC202 | Empirical Prototyping & Research Artifact Engineering in Robotics and Intelligent Automation | Practical | Construct the foundational computational artifact, reference architecture and experimental software testbed in Robotics and Intelligent Automation. |
| DOC203 | Advanced Statistical Learning & Model Evaluation in Robotics and Intelligent Automation | Theory | Derive generalization bounds, cross-validation asymptotics and high-dimensional estimation theory in Robotics and Intelligent Automation. |
| DOC204 | Field Experimentation & Data Collection Methodology in Robotics and Intelligent Automation | Practical | Deploy telemetry collectors, empirical logging probes and instrumentation across production testbeds in Robotics and Intelligent Automation. |
| DOC205 | Enterprise Systems Integration & Sociotechnical Impact Analysis in Robotics and Intelligent Automation | Theory | Analyze organizational adoption dynamics, human-in-the-loop interfaces and sociotechnical integration barriers in Robotics and Intelligent Automation. |
| DOC206 | Intellectual Property, Open Research & Technical Dissemination in Robotics and Intelligent Automation | Practical | Manage doctoral software patent disclosures, dual-licensing models and open-source scientific repository governance in Robotics and Intelligent Automation. |
| DOC207 | Technology Innovation Strategy & Industrial Research Collaboration in Robotics and Intelligent Automation | Theory | Structure university-industry research partnerships, industrial consortium agreements and technology transfer in Robotics and Intelligent Automation. |
| DOC208 | Mid-Candidature Doctoral Milestone & Progress Review in Robotics and Intelligent Automation | Theory | Successfully pass the comprehensive mid-candidature doctoral review demonstrating substantial empirical progress in Robotics and Intelligent Automation. |
| DOC209 | Applied Research Colloquium & Working Paper Series in Robotics and Intelligent Automation | Practical | Present working research papers, collect expert peer critique and author academic pre-prints in Robotics and Intelligent Automation. |
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| DOC301 | Doctoral Fieldwork & Experimental Artifact Evaluation in Robotics and Intelligent Automation | Practical | Conduct exhaustive empirical fieldwork and evaluate the research artifact across multi-organization deployments in Robotics and Intelligent Automation. |
| DOC302 | Comprehensive Data Analysis & Computational Verification in Robotics and Intelligent Automation | Practical | Perform advanced statistical triangulation, sensitivity analysis and algorithmic verification of empirical data in Robotics and Intelligent Automation. |
| DOC303 | Doctoral Dissertation Drafting: Architectural & Empirical Synthesis in Robotics and Intelligent Automation | Theory | Draft dissertation core chapters: theoretical foundation, artifact architecture and empirical findings in Robotics and Intelligent Automation. |
| DOC304 | Doctoral Dissertation Drafting: Results Validation & Benchmarking in Robotics and Intelligent Automation | Practical | Author dissertation comparative benchmark chapters validating novel contributions against state-of-the-art baselines in Robotics and Intelligent Automation. |
| DOC305 | Academic Journal Manuscript & Peer Review Preparation in Robotics and Intelligent Automation | Theory | Prepare high-impact peer-reviewed journal submissions conforming to top-tier ACM/IEEE editorial standards in Robotics and Intelligent Automation. |
| DOC306 | Industry Technology Transfer & Executive Briefing in Robotics and Intelligent Automation | Practical | Synthesize academic findings into actionable executive advisories and commercial technology transfer briefs in Robotics and Intelligent Automation. |
| DOC307 | Final Doctoral Dissertation Submission & Quality Audit in Robotics and Intelligent Automation | Practical | Complete the full academic dissertation manuscript and pass formal institutional originality audits in Robotics and Intelligent Automation. |
| DOC308 | Doctoral Oral Defense (Viva Voce) Preparation in Robotics and Intelligent Automation | Theory | Master academic rhetorical defense, anticipate committee objections and articulate unique scholarly contributions in Robotics and Intelligent Automation. |
| DOC309 | Final Executive Doctoral Defense & Research Dissemination in Robotics and Intelligent Automation | Practical | Successfully defend the doctoral dissertation in public viva voce examination and disseminate scholarly findings in Robotics and Intelligent Automation. |
Master’s degree in computing or related quantitative discipline with significant technology leadership experience. Research concept proposal required.
Brookfield School of Computing is an independent private education institution in formation. Academic programmes, entry requirements, fees and awards are subject to institutional review and applicable Swiss legal regulations.