Arendal, Agder, Norway
Hi, thanks for stopping by! I'm Markus, and I come from Arendal — a small town the southern coast of Norway. I hold a master's degree in neuroscience from EUCOR's tri-national 'JMN' program. And I most recently worked as a junior data engineer in Learning Machines GbmH, a data science consulting start-up company with a focus on sustainability. I have a broad academic background, and my interests are varied and many. I obtained my bachelor’s degree in biology (Molecular & Cellular) from Creighton University in the USA, graduating Magna cum Laude, with three additional minors: Biophysics, neuropsychology, and (analytic) philosophy. During my college days I wrote grade 'A' papers on quantum computing hardware, astrobotany/terraforming, biomedical ethics, metaphysics, and artificial intelligence, to mention a few. During my master's I focused on neuroprosthetics and neural networks, and ended up falling in love with computer programming and data science. I'm a passionate advocate for self-learning (especially using online resources), and a fierce critic of traditional lecture-style classroom learning. As a scientist, there are a few things that I believe uniquely sets me apart from the crowd: • I am exceptionally conscientious, meticulous, and methodical in my work. • I make a conscious habit of keeping a digital 'lab notebook' to capture all my thoughts, ideas, and meeting notes, so that nothing gets lost or forgotten. • I love the process of writing thorough and understandable documentation of computer code. • I always question the veracity of any claim lacking empirical evidence — that is, I am a skeptic at heart. As a person I’m jovial, sociable, and informal. I’m good at explaining complex ideas in simple terms, and I’m a ‘straight shooter’ with zero tolerance for technobabble, pretense, and obfuscation. I’m approachable, easy to talk to, and I work well with others, even as a remote online collaborator. If I sound like the kind of person you'd like to work with, drop me a line!
Branch: Sportshuset Outlet, Arendal Daily responsibilities: • Packed sporting goods from warehouse onto shelves • Kept the store tidy • Created displays for products • Greeted customers and provided assistance when asked • Rang up purchases Valuable skills and experiences: • Assembled several hundred pairs of cross country and alpine skis, and advised customers on choosing the right ski type, size, poles, bindings, etc. • Sharpened my social instincts for customer service and my ability to think on my feet to solve problems in a timely and efficient manner.
• Supervisor, CEO, and founder: Dr.-Ing. Boris La Worked in a small start-up using an Agile and DevOps methodology to create AI & Machine Learning solutions for wide-ranging applications Projects & Responsibilities: • Built infrastructure as code (IaC) with Terraform • Deployed cloud services using GCP and Kubernetes • Optimized AI engine performance by parellelizing computation with Dask • Protected python source code using Cython compilation • Automated containerized compilation for multi-platform wheels-distributions • Contributed multiple features to data transformation pipeline
• Supervisor and mentor: Prof. Dr. rer.nat. Ulrich G. Hofmann • Collaborator: Olaf Christ, M.Sc. • Master’s thesis: >> Measured thickness of glial sheaths in fluorescence histology images obtained from rats implanted with flexible neural probes >> Proposed and implemented novel parameters to quantify ‘thickness’ • Secondary project >> Topic: Using accelerometer-containing toys to measure rat activity >> Wrote scripts to analyze over 7000 hours of accelerometer raw data • Tertiary project (discontinued) >> Simulating neuronal response of a DBS probe using a FEM from COMSOL Multiphysics with the NEURON simulator
Laboratory for Biomedical Microtechnology • Supervisor: Prof. Dr.-Ing. Thomas Stieglitz • Mentors: Danesh Ashouri Vajari, M.Sc. and Maria Vomero, M.Sc. • Learned basics of MEMS manufacturing • Measured changes in dopamine concentration using fast-scan cyclic voltammetry (FSCV) • Assessed quality and performance of various thin-film neural probes by: >> Microscopy >> Cyclic voltammetry (CV) >> Electrochemical impedance spectroscopy (EIS)