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A scroll-driven story of biodiversity science and software development, told through the metaphor of git.
Biology 1 & Technology and Research Studies 1
Information Technology 1
Biology 2 & Technology and Research Studies 2
Information Technology 2
Semester 1: Autumn
Learning Tools for Biology
Semester 2: Spring
Learning Tools & App
Semester 3: Autumn
Founded: 18.01.2020
Web tools for the student biology organization
No longer available
Co-founded BioFactum, the student biology organization, and stepped into the IT role: building the website, creating digital tools, and shaping the online presence. The first time programming skills directly supported the field of biology.
Semester 4: Spring
Spring
Semester 5: Autumn
Autumn
Encountered real data-analysis challenges in ecology. R was new, but the logic wasn’t. High-school programming background resurfaced: loops, functions, debugging, problem-solving. R went from a requirement to a superpower.
Semester 6: Spring
Proportional differences of rodents and other prey in the Eurasian Eagle Owl’s diet
Semester 1: Autumn
Semester 2: Spring
Semester 3: Autumn
Semester 4: Spring
Presented my master thesis on Arctic horizon scanning and biosecurity.
Award from NTNU Natural Science Department. My master thesis was awarded as the best master thesis in sustainable development 2024.
Payload Engineer at OrbitNTNU BioSat: systems for plant growth in space. Work included 3D modelling/printing, sensor data, and leading a sub-team of 4. Design of supply systems (nutrients, water, light) and survival tests.
Norwegian University of Science and Technology
I continued to improve the Arctic Horizon Scanning Project under NTNU, using known vascular plant locations and climate data to model the climatic niche space of plants known to be alien throughout the world and identified overlaps in their climatic niche space with the Arctic.
A package for parsing botanical names to correct spelling errors and improve data quality.
Teacher
Personal and academic projects
The convergence ahead
All the ecological knowledge, field experience, and scientific methodology are in place. What remains is the backend foundation to build the tools that bring it all together.
Scalable systems for species occurrence, monitoring, and ecological datasets.
Backend services powering species distribution models, climate niche analyses, and risk assessments.
Sensor data ingestion, remote sensing, and nightly model updates. All require robust infrastructure.
Decision-support systems combining spatial data, ecological models, and stakeholder interfaces.
Platforms for public data collection with proper authentication, validation, and data integrity.
Enterprise Systems & Data Architecture
The missing foundation before biology and technology can fully converge. Frontend, tooling, and data science are strong, but building biodiversity platforms, ecological modelling APIs, and automated monitoring pipelines requires deep backend understanding.
How enterprise-grade systems are structured, maintained, and scaled for reliability and performance.
Relational databases, data modelling, backup/restore strategies, high-availability setups, and transactional consistency.
Identity management, role-based access, audit trails, and secure API communication. Essential for handling sensitive ecological data.
Deployments, monitoring, system checks, data migrations. The backbone of automated ecological workflows.
Tracing cause-and-effect across complex networks, diagnosing emergent problems, building stable and resilient architectures.
An open pull request representing the future direction, where both branches combine permanently. Biodiversity science powered by software engineering.
$ git merge --no-ff dev █