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  1. Programs
  3. Science Patent Law

Science Patent Law

University of Minnesota-Twin Cities

Master's DegreeAcademic

Become a contributor for free to openly demonstrate student outcomes, industry alignment & eligibility criteria.

The Master of Science in Patent Law is a professional master's degree for scientists and engineers interested in pursuing a career in the growing field of patent law. The program requirements may be completed in one year of full-time study or in two years (with an optional third year) on a part-time basis. This program is offered through the University of Minnesota Law School.

Credits

30 credits

Format

In-Person

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Program Pathways

Credentials this program stacks toward

No program pathways.

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Program Details

Detailed information about this program

No detailed information available.

Requirements

What you need to earn this credential

No requirements listed.

Financial Aid

Eligible funding programs

No funding information available.

Scholarships

No scholarships listed.

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Locations

Where this program is offered

  • Minnesota

    Minnesota

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Related Programs

Programs related to this one

No related programs.

Skills & Competencies

Skills developed through this program

Auto-populated·from O*NET via SOC 25-1021.00

Skills

InstructingReading ComprehensionWritingSpeakingActive LearningLearning StrategiesCritical ThinkingActive Listening

Knowledge

Computers and ElectronicsEducation and TrainingEnglish LanguageCustomer and Personal ServiceMathematics

Abilities

Oral ComprehensionOral ExpressionWritten ComprehensionWritten ExpressionDeductive ReasoningInductive ReasoningSpeech ClarityInformation OrderingNear VisionProblem Sensitivity

Tasks

  • Prepare course materials, such as syllabi, homework assignments, and handouts.
  • Compile, administer, and grade examinations or assign this work to others.
  • Prepare and deliver lectures to undergraduate or graduate students on topics such as programming, da

Technology

Web page creation and editing softwareGraphics or photo imaging softwareVideo creation and editing softwareComputer based training softwareData base user interface and query software

Tools

Carousel slide projectorsCompact digital camerasCompact disk CD playersComputer data input scannersComputer laser printersComputer projectorsConference telephonesDesktop computersDigital calculatorsDigital video disk DVD playersDigital video editorsHandheld microphonesHandheld videocamerasInteractive whiteboard controllersInteractive whiteboards

Work Values

AchievementIndependenceWorking ConditionsRecognitionRelationshipsSupport
Career Pathways

Occupations this program prepares you for

Auto-populated·from O*NET + BLS
Occupations matched to this program, with median wage, top wage, growth, and openings
SOCOccupationMethodWageGrowthOpenings
Match confidence: medium25-1021.00Computer Science Teachers, Postsecondarytitle_inference———
What You'll Learn

Key competencies developed through this program

Auto-populated·from NSX Competency Framework

Mastery: advanced (Level 4)(based on Master's Degree)

  • Departmental curriculum strategy and long-range academic program direction — set and lead in alignment with institutional mission, accreditation requirements, and emerging workforce needs in computing.
  • Faculty professional development initiatives in pedagogy and discipline currency — design and facilitate to elevate instructional quality across the full computer science teaching team.
  • Cross-disciplinary and interdepartmental curriculum collaborations — lead with colleagues in engineering, mathematics, and information systems to build integrated academic pathways for students.
  • Institutional policies governing academic standards, assessment practices, and program review — shape and advocate for at the college or university governance level as a senior faculty voice.
  • Grant proposals and externally funded research programs in computer science or CS education — originate, lead, and manage, directing junior faculty and graduate researchers toward scholarly impact.
  • Mentorship ecosystems for early-career faculty and doctoral teaching assistants — establish and sustain, modeling expert instructional practice and scholarly integrity across the department.
  • Accreditation self-study processes and program outcome assessments — lead comprehensively, synthesizing evidence of student learning to satisfy national accrediting body standards.
  • Emerging instructional technologies and pedagogical innovations — evaluate at an organizational scale and champion adoption strategies that transform learning experiences across multiple CS courses and cohorts.
  • Departmental and college-level resource allocation decisions affecting staffing, laboratory infrastructure, and technology procurement — inform and influence with deep expertise in computational education needs.
  • National and international professional communities in computer science and higher education — represent the institution through keynote presentations, editorial board service, and leadership in professional organizations.

Some details on this page are auto-populated from public workforce data sources: O*NET (opens in new tab), BLS (opens in new tab), College Scorecard (opens in new tab), DOL Training Provider Results (opens in new tab), NSX (opens in new tab). Provided in partnership with LER.me Career Intelligence.

Student Outcomes

Performance metrics for this program

Auto-populated·from Scorecard + DOL
Completion Rate
64%
Placement Rate
34%