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PhD Interview Presentation

Transcript: Interview for PhD position at University of Paris Academic Background Academic Background - High School Degree in Mathematics Chounen High School, 2016 - Bachelor Degree in Physics University of Djelfa, 2016-2019 - Master Degree in Astrophysics University of Constantine 1, 2019-2021 Courses Highlights M1 Courses First year of master degree Fundamental astronomy Astronomical data processing Interstellar medium computational physics general relativity Particle physics Courses Highlights M2 Courses Second year of master degree Standard model Astroparticle physics High-Energy Astrophysics Cosmic Rays Nuclear Astrophysics Vision Experience in data analysis Experience in correlation research Experience in scientific writing Experience in Python programming and Basic ML knowledge Why would I fit for this program Research Experience Research DRAFT Paper Algorithms Here are few algorithms used in my previous works correlation finder D'Agostni Fitting ML Algorithms Machine Learning Algorithms Support Vector Machines K-Nearest Neighbors Decision Trees Future Goals To do learn and develop machine learning algorithms for the search of neutrino-gamma correlations and analyze its data. Approach: - benefit from my previous experience -benefit from the AHE group -learn advanced machine/deep learning techniques THANK YOU

PhD Interview Presentation

Transcript: Interview for PhD position at Maastricht University Academic Background - BS in Computer Engineering (IT branch) Azarbaijan Shahid Madani University, 2013-2017 - MS Degree in Computer Engineering Bilkent University, 2019-2022 Academic Background BS Courses Highlights Artificial Intelligence Decision Support and Expert Systems Database Systems Discrete Mathematics BS Courses MS Courses Highlights MS Courses Machine Learning Deep Learning Computer Vision Computational Geometry Parallel Computing Research Experience Research Applying Information Retrieval Paradigms in NL to SQL Translation Conditional text generation for query recommendation Explaining multi-class classification results TranSQLate MS Thesis improve the accuracy by 16.5% Learning with additional feratures Transformers DRAFT Paper Data Scientist 1001Epochs Work Experience Used LLMs to paraphrase Question-Answering model using Langchain Similarity search Vision Experience in data analysis Experience in correlation research Experience in scientific writing Experience in Python programming and Basic ML knowledge Why would I fit for this program Trustworthy Explainiability, Transparency, Traceability Trustworthy Conversational AI Scale Blending skills personality, knowledge, empathy Generation strategies beam search, next token sampling, and n-gram blocking Conversational AI Future Goals To do learn and develop machine learning algorithms for improving the quality of chatbots and Conversational AI Approach: - benefit from my previous experience -benefit from the great research envirnment at UM -learn advanced machine/deep learning techniques THANK YOU

PhD Interview Presentation Template

Transcript: Why I Have Applied for a PhD Program Project 2 Overview Diving into [Project Name], I delved into [brief description of the research questions]. The methods utilized, such as [mention specific methods], led to [highlight significant outcomes]. This project enhanced my expertise in [mention relevant skills or knowledge areas]. Mostafa Gharbawi Dissertation project: Synchronisation of Heterogeneous Oscillators in Power Networks Introduction: Unveiling My Academic Journey With a background in [mention field], I am deeply passionate about [add specific research interests]. Through my academic journey, I have honed my skills in [mention relevant skills] and aim to make impactful contributions to the field of [mention field]. A Stable Power Network: Aim: Online integration of renewables into the grid, Eliminating environmental impacts. Challenges: Operational and inertial dissimilarity, system instability, Asynchronisation and frequency disturbance, Uncertainty in availability of natural resources. Prepared for the Next Chapter Personal Background: Studied Engineering Mathematics, Skillful in data modeling, Worked on numerous group projects, Helped my employer to increase revenue, Highly receptive, enthusiastic, and discipline. Envisioned Power Network: Project 1 Overview Solutions: Conventional power network model, Kuramoto model. Results: Synchronisation and stability equivalence, Quantifying network connectivity, Synchronous parametric conditions. Future work: Feasible synchronisation conditions, Locally merging green generators. Involvement in Other Group Projects Automation of Manual Tasks Early Prediction of Sepsis Disease Objective: Service Quality, End-user experience. Tools: Challenges: Data pre-processing, Missing clinical records, Effective approach. Binary Probabilistic Classification: Maximum a Posteriori method, Naive Bayes Theorem. Outcome: Reduced completion time to 20%, Streamlined journal process, Improved invoicing quality. Why Am I the Ideal Candidate for This Project? My educational background, Possess genuine passion for this field, Result-driven and pragmatic in approach, Responsible for my own academic development, Believe in AI as a tool for the betterment of humanity. Assignment Using MAP: Skills Acquired: Data quality assurance, Coding reproducibility, Collaboration & improvement, Interpersonal & communication. Final Results: THANK YOU FOR LISTENING Improved input data Increased success rate from 45-60% Any questions? mostafa.gh1989@gmail.com

PhD Interview Presentation

Transcript: Interview for PhD position at University of Antwerp Academic Background Academic Background High School Degree Exchange student in Canada for 6 months Master Degree in Physics Federal University of Pernambuco PhD in Physics Federal University of Penambuco Graduation in Physics Federal University of Pernambuco 2017-2019 2013 2020-2022 2022-2026 Courses Highlights Classical Electrodynamics Quantum Theory Statistical Mechanics Quantum Optics Master Courses Courses Highlights PhD Courses Advanced Classical Mechanics Computational Physics Magnetic Properties of Structures Advanced Classical Electrodynamics (ongoing) Teaching experience Experience teaching physics High School Teacher Colégio Fernando Ferrari High School Teacher Colégio Imaculado Coração de Maria Substitute Professor Federal University of Pernambuco Contract Professor Faculty of Igarassu 2021 2021 - 2023 2020 2023 High School Teacher National Commercial Apprenticeship Service - Senac 2023 Prizes Useful skills Checklist Experience using Latex for scientific writing Experience solving Monte Carlo and Molecular Dynamic simulation Data analysis using OriginPro and Gnuplot Experience using OOMMF and Mumax3 for simulation of magnetic reversal and FMR Programming skills using Bash Script, C, Octave and Python Research Research Experience Algorithms Some previous algorithms Monte Carlo Molecular Dynamic Mumax3 + Bash Results a) b) c) d) Draft Paper Dipolar magnetic interactions in 3x3 arrays of rectangular Ni nanopillars Simulations of FMR for study the shape anisotropy in square hollow nanopillars Effects of the packing factor on magnetic anisotropy in a 3x3 array of square hollow Ni nanopillars Simulated FMR to study in plane magnetic anisotropy of 3x3 array constituted by square base nickel nanopillars Future Goals Learn Density Functional Theory 01 Using DFT to find magnetic parameters Calculations using VASP 02 Learn and use VASP in simulations Improve my scientific writing skills 03 04 Objectives Study and enhance my knowledge to publish more scientific papers Contribute with my expertise and proactivity Use my previous experiences to contribute to my fellow's work and keep a good labor environment Questions? ?

PhD Interview Presentation

Transcript: PhD Interview Presentation Safety and Sustainability in Bio-based Composites' Structural Design Another point Remember to break up your words so your audience can follow. Academic Background Master's in Architecture, Building, and Planning (Eindhoven University of Technology) Specialization: Architectural Urban Design and Technology Thesis: Sustainable design of detached houses for extended Danish families Bachelor in Architecture (Sadjad University of Technology) Key Courses: Strength of Materials, Building Materials, Statics Willow Technologies, Ghana Source: Paul Yakubu. "Willow Technologies Transforms Agricultural By-Products Into Building Materials in Ghana" 28 Jul 2023. ArchDaily. Accessed 1 Jun 2024. <https://www.archdaily.com/1004645/willow-technologies-transforms-agricultural-by-products-into-building-materials-in-ghana> ISSN 0719-8884 Thank you for your time and consideration Skills and Competencies Technical Skills: Autodesk AutoCAD Autodesk Revit Rhinoceros 3D Adobe Creative Suite (InDesign, Illustrator, Photoshop) Python SQL SPSS Introduction Hasti Serajahmadi MSc in Architecture, Building, and Planning specializing in Architectural Urban Design and Technology BSc in Architecture Professional Experience Internship at UArchitects (May 2022 – Oct 2022) Collaborated on sustainable design projects and competitions such as MICROHOME Junior Architect/Assistant at Jam Silica Processing Company (Sept 2020 – Aug 2021)

PhD interview Presentation

Transcript: Input: Literature review Existing data sets Qualitative & quantitative data collected from case study regions Outputs: Create spatial framework Model various land use scenarios using framework at different spatio-temporal scales Present future scenarios in social ecological political contexts Glastir Woodland Creation Opportunities Phase 1 habitat map Project methodology Broadleaf woodland habitat network - Forest Research Various indexes: % cover, No. of patches, total edge, core area. Distribution of welsh woodland is spatially correlated rather than random and governed by topography, hydrology and land use (agriculture/plantation) Conifer plantations - highly correlated, broadleaf woodlands - less clustered Europe - percentage tree cover Ancient Woodland Inventory (2011) Northern forest Land cover thresholds (Forest Research) Peri-urban forest Afforestation - "50 million new trees" Urban/industrial and post-industrial landscape Shadows path of east-west M62 Biodiversity offsetting - masking woodland losses elsewhere? Only £5.7 million from Government from a projected total of £500 million Centre for Ecology and Hydrology - Land cover map 2015 Where can we see some of these drivers playing out in a UK context? Revive absent ecological processes Increase habitat connectivity. Core zones and buffer zones. Land already committed through NGO partners and public forest. Big change is bringing farmers onboard Precedents set by Pontbren project and MWT Pumlumon project (PES) Work on adapting commons concept Summit to Sea/O’r Mynydd i’r Môr Northern Forest Policy instruments Forest products markets Forest cultures Value of competing land uses Innovation - tech & skill Land abandonment Biodiversity - habitat protection Topography/Hydrology Thank you! Diolch yn fawr! Scale - at what spatio-temporal resolutions? Mapping between models and real world - applying landscape thresholds to random and actual landscapes. Modelling resilient, robust woodlands. "Crowded future landscapes" - competing land uses - woodland emergence within hostile matrix of intensive land use - disruption of open habitat networks. Interplay between spatial analysis and social research. Ethical dimension - respect for present landuse practice and social/cultural importance of this. Place spatial analysis within complex social ecological economic, politcal context. Before Adam Thorogood Summit to Sea Case studies 2016 Wales forest extent, loss & gain Land use change on a large scale involving multiple partners. Passive vs. Active afforestation National Forest Summit to Sea - terrestrial and marine, upland, agricultural Northern Forest - built environment, infrastruture, peri-urban National Forest - 28 years into project, peri-urban, afforestation Borders Forest Trust - Carrifran Wildwood, upland afforestation Knepp Castle - estate, ex-arable/dairy land, process-led wilding Trees for life - Scottish highlands, restore Caledonian forest Mersey Forest - community-led, partnership, peri-urban "Emerging spaces for native woodland growth in Britain's crowded future landscapes." Operationalising future planing PhD Interview presentation Adam Thorogood 10th Aug 2018 Useful Datasets What are the drivers and constraints for increase or decrease in forest cover? Trees for Life Slovenia forest extent, loss & gain Phase 1 habitat survey Ancient Woodland Inventory Glastir woodland creation opportunities Agricultural data sets - IBERS Sentinel 2 satellite data UK forest extent, loss & gain

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Transcript: Hossein Dehghan-Niri highly motivated, learner and explore for new ventures EDUCATION EXPERIENCE SKILLS Research hosseinniri@hotmail.com EDUCATION Bachelor Degree Electrical Engineering(Control major) subjects and courses: Linear\Modern\Digital\industrial... Control Simulation and implemention Controllers Simulation and Modelling Electrical machines and industrial electronics MCUs Programming and Circuit Design Programming (C\Cpp\Python) Machine learning KNTU University Address of the institution: Tehran City, Iran Master's Degree Electrical Engineering(Electrical Machines And Power Electronics) subjects and courses: Electrical Machines modeling and control System Identifications Optimal Control Converters Control and Design General Theory of Electrical Machines KNTU University Address of the institution: Tehran City, Iran EXPERIENCE 2016-2018 2017-2018 Undergraduate research assistant ARAS-KN2C Team Advanced Robotics and Automated Systems (ARAS) • Implementing Fuzzy-PID controllers for altitude and position control of quad-rotors • PCB and 3D Body Design of quad-rotor • Control and drive 3-phase BLDC motors • Planning and navigation control of outdoor quad-rotors by GPS • Embedded programming and work with MAV link protocol • Achieve third place in indoor MAVs in the Iranopen 2018 Robotic competition 2018-2020 2018-2020 KNTU Undergraduate Research Assistant Bachelor project: Parameter estimation of industrial winding (Damavand Tokamak) using an Output-only Observer/Kalman filter identification (O3KID) method Simulation Modeling course project: Modeling and Simulation of 3DOF Arm Using Co-simulation of Simscape and 3D model of SOLIDWORKS Freelance project: Sign detection using a classic computer vision method Computer Vision course project: Persian Handwriting Recognition using Convolutional Neural Network and Computer Vision Algorithm 2020-2023 2020-Present KNTU Advanced Electric Machines and Power Electronics Research Lab Graduate Research Assistant AMPE LAB Implementing speed controller of SPMSM with TI DSP C2000 series using SIMULINK Coder Analytical modeling of PMa-SynRM machine Torque ripple modeling using MLP ANN based on FEA data Torque ripple reduction of PMa-SynRM Using Harmonic injection optimized by Genetic Algorithm Torque ripple reduction of PMa-SynRM Using ANN torque ripple model estimator Teaching Assistance of Electrical Engineering Fundamentals Course Author and Co-author of four conference papers and one journal paper Adjacent instructor of electronic and control in robotic course 2020-Present KNTU Advanced Electric Machines and Power Electronics Research Laboratory Graduate Research Assistant Outcomes and Publications: AMPE LAB Publications: Thesis: "Torque ripple minimization of PMSMs using control algorithms" Novelty: "Develop model for output torque of PMSMs include torque ripple " PEDSTC2023: "Extended model of pm-assisted synchronous reluctance motor including torque fluctuation" Novelty: Propose ANN model for torque ripple use little data from FEM. ICEMD2023: "Torque fluctuation minimization in pma-synrm using optimized current harmonic injection by genetic algorithm" Novelty: Use ANN model of torque ripple as feedback for GA optimization. In preparing: "Torque ripple reduction in PMSMs using FOC aided by ANN torque ripple estimator" Novelty: Use ANN model of torque ripple model as estimator. SKILLS non-technical skills Soft Skills Native language Second language Persian English TOEFL : 86 Reading: 24 Listening: 24 Writing: 20 Speaking: 18 Other Skills Team-Working and Teaching Electrical Skills: Skills description: Electrical Machines Drive: Modeling, Control, Analysis Control Systems: Linear, Modern, Digital, Optimal Control Power Electronics: Design, Control, Analysis System Identification: Static, Dynamic, Nonlinear Experience in prototype development involving Designing, soldering, 3D printing, assembly, testing, and familiarity with mass production processes, including manufacturing, quality control, and supply chain management. Electrical Software Skills Skills description: COMPUTER Programming Languages: Python, C++, MATLAB for modeling, simulation, and data analysis. Simulation Tools: SIMULINK, LTSpice MCUs: STM32F and Ti C2000 series programming Design: PCB design with Altium Design 2D and 3D design using SOLIDWORKS Version Control: GIT and SVN Machine Learning & AI: familiar with machine learning frameworks such as Tensorflow, Keras, Opencv My Hobbies Hobbies description: Hiking and biking Traveling Movie and Persian Music Entertainments Research Present status of my research progress: Verify my thesis by Implement on hardware and publish result in journal paper Research interest: Actively involved in developing control algorithms to optimize drive and power electronics systems, and implementing them on hardware.

PhD Interview Presentation

Transcript: My profile Thank You! Academic Background Academic Background - B.Tech, Department of Electronics and Communications Engineering Jawaharlal Nehru Technological University Kakinada, 2017-2021 - Research assistant, Department of Neuroscience University of Geneva, 2021-Present To develop low complex ML/DL algorithms for various disease detections using biomedical signals. The primary focus of my reseach is on neuro and cardio signals (EEG and ECG). Vision Research Research Experience Published Papers Under Review Papers Algorithms Here are few algorithms used in my previous works Decomposition Algorithms Singular Spectrum Analysis Discrete Wavelet Transform Wavelet Packet Decomposition Intrinsic Time-scale Decomposition Dimensionality Reduction Principal Component Analysis Kernel Principal Component Analysis Sub-Pattern based PCA Independent Component Analysis Linear Discriminant Analysis Autoencoders ML/DL Algorithms Machine Learning Algorithms Support Vector Machines K-Nearest Neighbors Decision Trees Deep Learning Algorithms CNN's LSTM-RNN's Transfer Learning To do research and develop computationally cheap machine/deep learning algorithms for the applications of biomedical signal processing. Approach: - To replace all the statistical feature selection techniques with learn-able feature selection algorithms. - To increase the use of deep learning for the extraction of multi-variate features from biomedical signals. Future Goals

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