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Master’s in Deeptech Startup Valuation Engineering

Online master's programme of 1,900 hours in deeptech startup valuation engineering: 12 modules covering the deeptech ecosystem, early-stage valuation methods, risk-adjusted DCF, real options, intellectual property, market sizing, investment structures, technology due diligence, exits and regulation, with an assigned technical tutor.

Duration1900 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Characterise the risk and capital profile of deeptech companies.

02

Apply valuation methods for pre-seed and seed stages.

03

Build rNPV and real options models for technology projects.

04

Value patents and other intangible assets.

05

Size markets and business models for emerging technologies.

06

Analyse term sheets and investment structures.

07

Carry out technology due diligence and issue investment recommendations.

Profile

Who it's for

  • Deeptech venture capital analysts.
  • Technology transfer managers at universities and research centres.
  • Valuation consultants.
  • Startup chief financial officers.
  • Investment fund managers.
  • Intellectual property analysts.
  • Engineering or science graduates aiming to move into venture capital.
Standards & tools

What you'll work with

  • IPEV Valuation Guidelines (private capital valuation)
  • IFRS 13 (fair value measurement)
  • Spanish Act 28/2022 (Startups Act)
  • Regulation (EU) 2019/452 (screening of foreign direct investment)
  • ISO 16290:2013 (technology readiness levels)
  • Regulation (EU) 2019/2088 (SFDR) (sustainability-related disclosures in financial services)
  • Regulation (EU) 2021/821 (dual-use items export control)
  • Microsoft Excel
  • Carta
  • Python
  • PitchBook
  • Questel Orbit
Syllabus

12 modules · 1900 h

  1. 1.1Characteristics of deeptech companies
  2. 1.2Science, engineering and technology transfer
  3. 1.3Quantum, biotechnology and new materials
  4. 1.4Long cycles and capital intensity
  5. 1.5Technology and manufacturing readiness
  6. 1.6The European and Spanish ecosystems
  7. 1.7Investors specialising in deeptech
  8. 1.8Technology risk versus market risk
  9. 1.9Success and failure stories
  10. 1.10Case study: risk profile of a photonics startup
  1. 2.1The difference between value and price
  2. 2.2Methods for early stages
  3. 2.3Pre-money and post-money valuation
  4. 2.4Dilution and the cap table
  5. 2.5Venture capital discount rates
  6. 2.6Required returns by stage
  7. 2.7Illiquidity premium
  8. 2.8Biases in early-stage valuation
  9. 2.9International IPEV Guidelines
  10. 2.10Exercise: cap table after three funding rounds
  1. 3.1Berkus valuation method
  2. 3.2Payne scorecard method
  3. 3.3Risk factor summation
  4. 3.4Venture capital method
  5. 3.5First Chicago scenario method
  6. 3.6Private transaction comparables
  7. 3.7Valuing the founding team
  8. 3.8Milestones and progressive de-risking
  9. 3.9Cost to reproduce the technology
  10. 3.10Workshop: pre-seed valuation with several methods
  1. 4.1Projections for pre-revenue companies
  2. 4.2Revenue models for emerging technologies
  3. 4.3Discount rates by stage
  4. 4.4Risk-adjusted NPV and probability of success
  5. 4.5Adjusting for technical risk
  6. 4.6Terminal value and exit scenario
  7. 4.7Scenarios and Monte Carlo simulation
  8. 4.8Capital requirements and cash burn
  9. 4.9Limitations of DCF in deeptech
  10. 4.10Lab: rNPV model of a biotech company
  1. 5.1Managerial flexibility as a source of value
  2. 5.2Options to abandon, expand and defer
  3. 5.3Binomial valuation trees
  4. 5.4Black-Scholes applied to R&D
  5. 5.5Staged compound options
  6. 5.6Volatility of technology projects
  7. 5.7Decision trees with probabilities
  8. 5.8Integrating real options and rNPV
  9. 5.9Communicating value to investors
  10. 5.10Exercise: real options of a pilot plant
  1. 6.1Patent protection strategy
  2. 6.2Freedom-to-operate analysis
  3. 6.3Income-based patent valuation
  4. 6.4Royalties and technology licences
  5. 6.5Relief-from-royalty method
  6. 6.6Trade secrets and know-how
  7. 6.7Licensing from universities
  8. 6.8Patent portfolio analysis
  9. 6.9Infringement risk and litigation
  10. 6.10Case study: valuation of a patent family
  1. 7.1TAM, SAM and SOM market sizing
  2. 7.2Technology adoption curves
  3. 7.3Deeptech business models
  4. 7.4Industrial partners and co-development
  5. 7.5Regulatory barriers to entry
  6. 7.6Scaling up manufacturing
  7. 7.7Unit cost and learning curves
  8. 7.8Competing and substitute technologies
  9. 7.9Validation with early customers
  10. 7.10Workshop: market for a solid-state battery
  1. 8.1Pre-seed, seed and Series A rounds
  2. 8.2Convertible notes and SAFEs
  3. 8.3Liquidation preference
  4. 8.4Anti-dilution clauses and ratchets
  5. 8.5Shareholders' agreements and governance
  6. 8.6EIC Accelerator and CDTI funding
  7. 8.7Corporate venture capital
  8. 8.8Venture debt and participating loans
  9. 8.9Investor syndication
  10. 8.10Exercise: analysis of a term sheet
  1. 9.1Assessing technology readiness
  2. 9.2Scientific review and reproducibility
  3. 9.3Scalability and manufacturability
  4. 9.4Capabilities of the technical team
  5. 9.5Product regulation and certification
  6. 9.6Supply chain risks
  7. 9.7Strength of the intellectual property
  8. 9.8Data and software review
  9. 9.9Due diligence report
  10. 9.10Case study: due diligence of a quantum startup
  1. 10.1Acquisitions by strategic buyers
  2. 10.2Technology IPOs
  3. 10.3SPAC mergers
  4. 10.4Secondary market sales
  5. 10.5Exit multiples by sector
  6. 10.6Optimal exit timing
  7. 10.7Acquisition pricing and synergies
  8. 10.8Earn-out clauses
  9. 10.9Returns for founders and investors
  10. 10.10Lab: distribution waterfall in a sale
  1. 11.1Spanish Startups Act 28/2022
  2. 11.2Tax incentives for investment
  3. 11.3Foreign direct investment screening
  4. 11.4Dual-use technologies
  5. 11.5ESG criteria in venture capital
  6. 11.6Impact measurement
  7. 11.7SFDR disclosure for funds
  8. 11.8Responsible research and innovation
  9. 11.9Periodic reporting to investors
  10. 11.10Case study: investment screening in a funding round
  1. 12.1Selection of the startup to study
  2. 12.2Technology and readiness analysis
  3. 12.3Market analysis
  4. 12.4Ten-year financial projections
  5. 12.5Valuation using several methods
  6. 12.6Real options and scenarios
  7. 12.7Proposed investment structure
  8. 12.8Investment recommendation
  9. 12.9Master's Thesis report
  10. 12.10Master's Thesis: defence before a panel
Methodology, software & labs

How you'll learn

100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within the intake, so the programme is compatible with work.

Each module combines theory, guided reading of the original guidelines and regulations, and applied exercises. The working software is Microsoft Excel, Carta, Python, PitchBook and Questel Orbit, in free, academic or evaluation versions. Exercises are built on real procedures: valuing a startup with several methods, technology due diligence and analysis of a term sheet. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: IPEV Valuation Guidelines, IFRS 13, Spanish Act 28/2022, Regulation (EU) 2019/452, ISO 16290:2013, Regulation (EU) 2019/2088 (SFDR), Regulation (EU) 2021/821.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of the IPEV Guidelines, IFRS 13 and ISO 16290 applied to real cases, not as a theoretical annex.
Industry software:Microsoft Excel, Carta, Python, PitchBook and Questel Orbit, in free, academic or evaluation versions.
Master's Thesis with defence:A complete multi-method valuation and investment recommendation for a real deeptech startup, defended before a panel.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Technology and market analysis
Select the startup and analyse its technology readiness and market.
Financial projections
Build ten-year financial projections for the company.
Multi-method valuation
Value the startup using several methods, real options and scenarios.
Investment structure
Propose the investment structure and issue an investment recommendation.
Master's Thesis
Present the complete valuation study, defended before a panel.
Career opportunities

Where this takes you

Deeptech venture capital analystTechnology transfer managerValuation consultantStartup chief financial officerInvestment fund managerIntellectual property analyst
Admissions & scholarships

Requirements

  • University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
  • Internet connection and a computer capable of running the programme software.
  • English sufficient to read technical standards.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

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FAQ

Frequently asked questions

The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.

You work with Microsoft Excel, Carta, Python, PitchBook and Questel Orbit, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.

A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.

Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.

A university degree in engineering, science or architecture (or equivalent professional experience), a suitable computer and English sufficient to read technical standards.

Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.

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