The Computational Medicine Laboratory (CML) at the University of Houston is currently looking to recruit one or two highly motivated and creative Ph.D. students with applied mathematics and/or signal processing background to develop mathematical algorithms for biomedical engineering applications. CML mainly focuses on designing control, optimization, estimation, signal processing, and machine learning algorithms for biomedical and neural engineering applications. The ideal candidate has obtained their B.S. degree in electrical engineering (or related fields, e.g. mechanical, computer or biomedical engineering, computer science, applied mathematics, statistics, etc.) focusing on control theory and/or signal processing. The projects involve algorithm design and validation in real-time experiments with human recordings.
Interested candidates should contact Dr. Rose Faghih at firstname.lastname@example.org with the following required documents.
2) A statement of purpose that discusses the candidate’s academic achievements, previous researchexperiences, research interests, and projected professional goals. Also, to learn more about the CMLresearch projects, interested candidates should read the following open-access papers and in two paragraphs summarize/discuss the cortisol problem and the candidate’s understanding of the methodology used in the referenced papers and the insights the candidate gained from the results of the referenced papers:
3) Below is a simple MATLAB exercise related to one of the above cortisol papers that should be completed by candidates interested in the Ph.D. openings at CML:
The data file includes an impulse train input (u) measured at times tu and noisy measured impulse response output (y) measured at times ty. The input u and the output y are as defined in the model in “Deconvolution of Serum Cortisol Levels by Using Compressed Sensing.” Using MATLAB, please find the model parameters θ1 and θ2 using the input and output time-series, and then, estimate the output y using input u and the estimated model parameters θ1 and θ2. Please note that the time-series y is simulated skin conductance data (not cortisol measurements), and the constraints on θ1 and θ2 given in the paper (for cortisol) don’t hold for this time-series.
Your response should include your MATLAB code and a document that includes (i) a figure that shows the observed output (y) as well as the estimated output (the estimated output should closely match the observed output y), (ii) the estimated model parameters and (iii) a brief description of your approach.
4) Electronic copy of unofficial transcript(s). Recommended GPA≥ 3.5/4.0.
5) GRE and TOFEL (if applicable) scores. Recommended GRE scores: Verbal of 151, Quantitative of 164, and Analytical Writing of 4.0. Recommended TOEFL score: 99.