Crass_Oscillator said:Quantum computing is currently in what appears to be a growth phase, although it's significantly smaller than machine learning. ML is essentially "statistical modeling for CS majors", and many groups use biology as an application area for ML models. Have you considered that option?
Simulation and model science is a field of study that uses computer programs to replicate and analyze real-world systems or phenomena. It involves creating mathematical models and using computational techniques to simulate how these models behave under different conditions.
Simulation and model science is used in a wide range of research fields, such as physics, biology, economics, and engineering. It allows scientists to test hypotheses, understand complex systems, and make predictions without having to conduct costly or time-consuming experiments.
Quantum computing is a type of computing that relies on the principles of quantum mechanics to perform calculations. Unlike classical computers, which use bits to store and process information, quantum computers use quantum bits (qubits) that can exist in multiple states simultaneously, allowing for more complex and efficient calculations.
Quantum computing is different from classical computing in several ways. Quantum computers use qubits, which can be in multiple states at once, while classical computers use bits, which can only exist in a 0 or 1 state. This allows quantum computers to perform certain calculations much faster and more accurately than classical computers, especially for complex problems.
Quantum computing has the potential to revolutionize many industries and fields, such as cryptography, drug discovery, financial modeling, and machine learning. It can also help solve complex problems in physics and chemistry that are currently beyond the capabilities of classical computers.