Materials Scientist
Research and develop metals, polymers, ceramics and composites for new products.
Study matter, energy and forces through experiments, theory and simulation.
Physicists design experiments or computer simulations to test how particles, materials, light or energy behave, analyze the measurements, and publish the results or apply them to devices such as lasers, sensors and medical scanners. They use advanced math, programming in Python or C++, and specialized lab instruments. Research positions require a PhD in physics after a bachelor's degree.
Take these courses in order, from beginner to mid-level.
The shared base every STEM career uses: working with numbers and units, testing ideas fairly, handling data and code, and explaining your work.
How chemists, physicists and materials scientists work: the science and math core, units and estimation, the research path, and how to read and record science.
The everyday computer, internet, safety and AI skills every tech and STEM job assumes you already have.
Write clear emails and documents, present and run meetings, work well on teams, and navigate résumés, interviews and networking.
The practical math behind tech and STEM work: numbers, algebra, functions, geometry, logic and counting, with short code exercises.
Learn to program in Python from zero: values, decisions, loops, functions, data structures, files, modules and a small data project.
Describe data, reason with probability, and draw honest conclusions from samples, with short fill-in-the-blank Python exercises.
Recognise lab hazards, read GHS labels and Safety Data Sheets, choose PPE, and understand the training and records that keep labs safe.
The calculus and linear algebra behind science, engineering and machine learning: derivatives, integrals, vectors, matrices, gradients and eigenvalues, with Python exercises.
The physics behind engineering and the physical sciences: motion, forces, energy, momentum, torque, circuits, induction, waves and heat, with Python exercises and a home pendulum lab.
Use NumPy arrays, plots, fitting, numerical methods, units and instrument data files to do real engineering and science calculations in Python.
Learn DC and AC circuit analysis, power factor and three-phase basics, safe measurement on battery circuits, simulation, transformers, motors and systematic troubleshooting.
Special relativity, quantum and nuclear physics, Monte Carlo, orbit and PDE solvers, fitting with uncertainties, data acquisition and research computing, all in Python.
Research and develop metals, polymers, ceramics and composites for new products.
Analyze substances and develop new compounds, materials and products.
Study the chemical and physical processes inside living cells.