Noor Aldeen Almusleh

GPA–84.5% (Excellent), with first-class honors.

This is a four year program with a fast track option delivered in English as the language of instruction. Relevant modules studied include Quantum Physics I (87%), Quantum Physics II (94%), Thermodynamics (90%), Statistical Mechanics (95%), Electricity and Magnetism I (74%), Electricity and Magnetism II (77%), Mathematical Physics I (94%), Mathematical Physics II (89%), Mathematical Physics III (95%), Astrophysics (98%), Nuclear Physics (80%), and Particle Physics (94%).

Final year dissertation ”Heavy Quarkonium Mass Spectra From Complex Potential”; this study was an attempt to improve our understanding of the heavy mesons (such as the bottomonium) by studying the solution of the relativistic Schrodinger equation for some complex potential. This project took five months and it was supervised by Dr. Ahmed Al-Jamel.

Completed the two-week intensive course which covered many topics in quantum computing such as Deutsch-Jozsa Algorithm, Grover’s Algorithm, quantum classifiers, Quantum Approximate Optimization Algorithm (QAOA), quantum fidelity, and quantum hardware, completing all graded lab work assignments with a final cumulative score of 100%, demonstrating applied understanding and comfort with and about Quantum Computing and Quantum Machine Learning using Qiskit.

Using different Python libraries and frameworks to develop machine learning and deep learning models such as SciKit-Learn, Keras, and TensorFlow, to predict fraud, paddy disease, and classify images. To optimize my models, exploratory data analysis was my first approach, using Pandas, Scipy, and Numpy, and by utilizing static and interactive visualizations using Matplotlib, Seaborn, Dash, and Plotly I can decide what type of data augmentation or dimensionality reduction I should use. Finally, deploy these models to the internet using Flask (see for example:).

Develop websites using HTML, CSS, Bootstrap, Flask, and Jinja where I deploy my machine learning and deep learning models alongside with explanations of the model itself and its development alongside visualizations of the data.

Use different quantum algorithms such as VQE, QAOA, and QSVM to solve finance, chemistry, and optimization problems, as well as test quantum gates fidelity, training quantum circuits using gradient descent, using quantum kernels, and support vector machines. This was accomplished using Qiskit and IBM quantum lab with five qubits and using some quantum simulators such as QasmSimulator, StatevectorSimulator, and UnitarySimulator.

Using $\\LaTeX$ to edit scientific scripts that were published in peer reviewed journals, and writing my thesis using TexMaker editor, and Overleaf.

Enhanced vocal and written commutation skills through working as an educator as this role required high-level communication skills and clear presentations to communicate with students and the management. Also, completing a dissertation and writing up numerous projects at university and research (including the publishing procedure and what it requires of communication by email) helped develop more written communication skills.

Successful organization of science events for Phi Science Institute and the Ministry of Education (UAE) relied on effectively working with all volunteers. Understanding the importance of proactively developing relationships with others, sharing information, and supporting contributions from team members, which were then applied while working with a research group, helped develop excellent teamwork skills in academia.

Our main focus was on studying the spectrum of different sample stars to predict different physical properties of those stars. Using statistical methods, and relevant Python libraries (such as Astropy, Numpy, and Matplotlib) to study the spectrum of a few stars, their abundances, and their kinematics which helped in constructing an action space map that indicates the eccentricity and the spherical coordinates for the sample stars from our study and the literature. Based on that we recommended further observations to expand the sample used in these two studies to better predict these stars progenitors.

Conducted a theoretical study of a Cornell-like potential with the linear term being imaginary (that is, $V(r) = iar + b/r$). Finding the exact solution of such potential could assist in describing the behavior of heavy-quark mesons (e.g. bottomonium and charmonium).

Teaching AP Physics algebra and calculus based for grads 9, 10, 11, and 12 using English as the language of instruction. I worked in different classroom setups including traditional, online, and hybrid classrooms. Working as a teacher with the Emirates Schools Establishment involves creating lesson plans, in class activities, and arranging field trips. Furthermore, I supervise students who participate in science fairs, and create support plans for lower-achievers and execute those plans in cooperation with their parents. During my time as a teacher, I had the opportunity to work across multiple teams from different backgrounds and roles. We planned to do cross-subject activities and plan the general trend for our lessons to help students relate between different subjects (such as chemistry and physics, or physics and mathematics, etc.)

Completed four challenges, two foundational, one intermediate, and one advanced, using Qiskit while studying some related papers. These challenges were focused on Variational Quantum Eigensolver (VQE), Quantum Approximate Optimization Algorithm (QAOA), Quantum Support Vector Machine (QSVM), and Qiskit Runtime. The challenges were, in order, Optimizing your portfolio with quantum computers (finance), Band gap calculation of OLED molecules (chemistry), Image classification by QSVM (machine learning), and Battery Revenue Optimization (optimiztion).