The Optimization Intern will become a part of the RefleXion Algorithms team, and work in collaboration with RefleXion engineers and scientists to develop new features and expand existing capabilities of RefleXion treatment planning system. The various projects will involve convex optimization, image processing, measurement data processing and analysis, and system simulation.
This position requires working knowledge of simulation tools, signal and image processing fundamentals, related mathematical fundamentals including linear algebra, and will require analyzing and improving existing algorithms for solving complex problems in next generation radiation treatment planning and delivery.
The outcome of all radiation cancer treatments is dependent on the underlying cancer biology and the dose distribution delivered to the patient. RefleXion's patented biological guidance represents a revolution in radiation delivery that enables the underlying cancer biology to control and shape the therapeutic tumor dose. Treatment Planning Optimization Intern will participate in projects that make this possible, and which are critical to the development of RefleXion’s revolutionary cancer treatment machine.
Developing new features for RefleXion radiotherapy treatment planning optimization and dose calculation engines.
Developing automated validation suites for radiotherapy treatment planning optimization.
Working with Physics team to analyze dose measurement results for dose calculation validation or imaging processing.
Analyzing algorithm convergence and proving important mathematical properties.
Simulation tools such as MCAT or XCAT
Reading research papers, technical briefs, whitepapers and analyzing algorithms requirements and tradeoffs, and quickly generating Matlab prototypes
MS. or Ph.D. in engineering field with focus on math and experience in software engineering.
Working knowledge of convex optimization, signal processing basics (Fourier transforms, shift-invariance, and sampling theorem), and math fundamentals including linear algebra.
Published original research work involving the above.
Experience in Matlab
Experience with C++
Background in parallel programming, data structures, and big-O cost analysis.
Excellent communication, presentation and documentation skills.