Quantum Chemistry Computational Research

@PINESCRIPTERR

Hi, I understand you need a rigorous and reproducible computational chemistry workflow to turn your target molecules and property checklist into reliable, publication-ready results. I can handle ab-initio/DFT calculations using Gaussian, ORCA or a suitable equivalent, including geometry optimization, convergence verification and extraction of reaction energies, charge distributions and spectroscopic properties. I’ll keep the workflow reproducible with clearly commented input files, documented computational settings and organized outputs. I’ll also provide parsed results in CSV/Excel format and a concise methods report covering the selected functional, basis sets, convergence criteria and computational approach. Any unusual convergence behaviour, anomalies or meaningful trends will be highlighted rather than simply reporting raw results. Where useful, I can automate repetitive calculations and result extraction with Python notebooks, including workflow checks and structured data processing. Excited-state calculations can also be incorporated if required. Questions: 1. Which molecules and electronic properties are included in the first batch? 2. Do you have preferred functionals/basis sets or should I recommend them based on the systems? 3. Are excited-state calculations and Python workflow automation required for the initial two-week batch? Best regards, Houssame

@dataspro

Nice to talk you , After reading in detail the requirements of your project and concluding that they match my areas of knowledge and skills, I would like to introduce myself. My name is Anthony Muñoz and I am the lead engineer for DS Pro IT agency. I have worked for over 10 years in Backend and software development and have successfully done multiple jobs. It will be a pleasure to work together to make your project a reality. Please feel free to contact me. I´m looking forward to working with you. I really appreciate your time and remain attentive to any request or question. Greetings

@mcollinscalz

Hello my name is Collins and I can step right into your computational workflow to deliver rigorous, publication-ready quantum chemistry data. With extensive expertise in DFT and ab initio methodologies using both Gaussian and ORCA, I regularly handle geometry optimizations, reaction energies, charge distribution analyses (NBO/ESP), and spectroscopic signatures. To streamline your manuscript drafting, I will provide meticulously validated input decks, comprehensive convergence checks, and structured CSV/Excel summary tables. I am also highly comfortable handling excited-state calculations (TD-DFT) and automating repetitive computational pipelines using Python notebooks to accelerate data extraction and analysis. The deliverables will include clean input decks, raw and parsed output data, a concise 1-to-2-page methods report detailing functionals, basis sets, and dispersion corrections, alongside insightful commentary on any electronic or structural anomalies observed. I can comfortably meet your two-week turnaround for the first batch of molecules and look forward to building a seamless workflow for your research. Send over the structures and target checklist, and we can begin immediately.

@NelisThuo

Hello, I am a graduate in Chemistry with experience in computational chemistry, scientific research, and quantitative analysis of molecular and electronic properties. I can develop a reproducible workflow around your target molecules, beginning with structure validation and geometry optimization before moving to the required electronic-property calculations. I would select computational methods according to the molecular systems and properties being investigated, with appropriate attention to functional/basis-set suitability, spin state, SCF convergence, geometry convergence, and frequency or other validation checks where required. The workflow can be implemented in Gaussian, ORCA, or another suitable package, with clearly documented input files so every calculation can be reproduced. I can organize the resulting energies, charge distributions, spectroscopic data, and other observables into structured CSV/Excel outputs and provide concise interpretation of trends or anomalous results. Python notebooks can also be used where automation and consistent batch processing would improve reproducibility. The first batch can be structured around your two-week target, subject to the number and complexity of molecules and calculations involved. Could you share the target molecules and the specific properties you need calculated? Also, do you already have a preferred functional/basis set or computational level, and are excited-state calculations such as TD-DFT required?

@AnjosGustavo

Hi, This project strongly fits my background in mathematical modeling, scientific computing, and data-driven engineering. As a Senior ML/Data Scientist, I’m comfortable turning mathematically demanding research problems into rigorous, reproducible computational workflows. My approach would be systematic: validate structures - define appropriate DFT/ab-initio methods and basis sets - run geometry/convergence checks - extract target observables - automate parsing and analysis in Python - deliver publication-ready, traceable results. A strong foundation in mathematics, probability, optimization, and numerical methods helps me reason carefully about convergence, model assumptions, numerical stability, and unexpected results rather than treating computational packages as black boxes. I also bring strong Python/data engineering skills for workflow automation, structured CSV/Excel outputs, visualization, and reproducibility. Continuous learning is central to how I work, especially with research-driven problems. Best, Gustavo

@bizvivo

Hello, I am a Python‑savvy researcher with strong expertise in ab‑initio and DFT workflows using Gaussian, ORCA, and comparable packages. Your requirement to move from target molecules and property outlines to publish‑ready, reproducible data aligns perfectly with my background in computational chemistry and automation. Approach: Build validated input decks with clear, well‑commented files. Perform geometry optimisations, convergence checks, and extract observables (reaction energies, charge distributions, spectroscopic signatures). Parse outputs into CSV/Excel for seamless integration into your manuscript. Deliver a concise methods report (1–2 pages) detailing basis sets, functional choices, and convergence criteria. Highlight anomalies or trends with short discussions. Bonus Skills: Comfortable with excited‑state calculations (TD‑DFT, CIS). Experienced in Python notebook automation for batch runs, parsing, and reproducibility. Value: You’ll receive a rigorous, transparent workflow with reproducible results, ready for publication. First batch turnaround within two weeks, with potential for extended collaboration. Best regards, Suyash – Computational Chemistry & Automation Specialist

@engruhulajom

Dear Client, I’m a Top Rated, 5 Star full-stack developer with over 10 years of experience building data-driven applications, automation workflows, and reliable computational tools. I understand you need a reproducible quantum chemistry workflow covering ab-initio and DFT calculations, geometry optimisation, reaction energies, charge distributions, and spectroscopic properties. I can help organise validated input files, parsed CSV/Excel results, convergence checks, and concise methods documentation for your manuscript. My skills include Python, automation, data processing, databases, and technical documentation. Could you share the target molecules, required properties, and preferred quantum chemistry package? Best regards, Md Ruhul Ajom

@ZohaibSathio

Hi, DFT and ab initio runs on your target molecules, with the output parsed into something you can drop into the manuscript. Convergence is usually where these stall, not the chemistry. How I would do it: ORCA for geometry optimisation, a frequency check on each structure so no imaginary modes slip through, then cclib in Python parsing energies, charges and spectra into one CSV per batch. Which functional are you set on? The automation half is my strong side: batches of output files into one clean dataset. Regards, Zohaib

@DeMit19

Hi there I understand you need support with computational quantum chemistry workflows to generate reliable and reproducible research data. I have experience with scientific computing, Python automation, data analysis, and computational research workflows. I can help prepare calculation inputs, organize DFT or ab-initio workflows, analyze outputs, extract molecular properties, and provide structured results with clear documentation. I can assist with geometry optimization, energy calculations, charge analysis, convergence checks, and result summaries suitable for research reporting. My approach focuses on reproducibility, accurate workflow setup, and well documented computational results. Budget : $11 USD/hour timeline : 14 days Q1 : Which quantum chemistry packages and computational resources are currently available for the calculations? Q2 : Which molecules and target properties should be prioritized for the first calculation batch?

@svantem

Hello, Greetings , Good morning! I am an expert mobile software engineer with skills including Data Science, Quantum Computing, Scientific Research, Chemical Engineering, Data Analysis, Python, SPSS Statistics and Research Writing. Please send a message to discuss more regarding this project. Looking forward to serve you

@marvind18

You need a rigorous, reproducible quantum chemistry workflow that turns your target molecules into validated DFT and ab-initio results ready for analysis and manuscript use. My strongest match is the computational and automation side of this work. I have 9+ years of Python and scientific data-processing experience, including building automated workflows, parsing results, and producing structured datasets. I can build Python-based workflows around Gaussian, ORCA, or your preferred package, with organized input decks, convergence checks, parsed CSV/Excel outputs, and reproducible notebooks. I can also document functional and basis-set choices, convergence criteria, calculation settings, and anomalies so the workflow is easy to reproduce. For excited-state calculations, I can incorporate the required workflow once the target properties and software are confirmed. Could you share the number of molecules/reaction pathways and the specific properties you need for the first batch?

@danielw319

·:¨༺ I'M ALWAYS WITH YOU ༻¨:· ### Part 1 , Understanding / Observation The tricky part here is turning a handful of ab-initio and DFT runs into a clean, reproducible workflow you can drop into a manuscript. The goal is validated input decks for each molecule or pathway, robust convergence checks, and concise results that slot straight into your draft. ### Part 2 , Relevant Experience Proof Case in point: a pharma/biotech project where Gaussian 16 and ORCA were used to optimize 6 drug-like molecules. I delivered 6 validated input decks, CSV outputs with reaction energies and charge distributions, and a 1-2 page methods note. The main challenge was inconsistent SCF convergence across molecules; we fixed it by a controlled basis-set sequence (def2-TZVP and diffuse functions) and explicit convergence criteria, with a Python notebook parsing outputs into a single CSV. ### Part 3 , Practical Thinking For large batches, a small queue and chunked parsing helps. A tradeoff is extra convergence tweaks may add CPU time, but it yields reliable, publishable data. Hidden complexity includes aligning energy zero across Gaussian and ORCA, and keeping the workflow maintainable with clear logging and documentation. If needed, I can extend the pipeline to TD-DFT excited states later. ### Part 4 , Natural Reply Trigger I’ll tailor the initial batch to your targets and output conventions, and keep a concise methods note that can go straight into the manuscript.

@abhilashr53

I can deliver 'Quantum Chemistry Computational Research' end to end — clean architecture, tests, and deployment. I'll start with a short plan, share progress daily, and hand over production-ready code. Could you confirm your timeline and must-have features so I can lock the scope?

@damiann11

Hello, I am a Chemical Engineering Thermodynamics expert with strong experience in computational chemistry and molecular property analysis. I can develop a rigorous, reproducible workflow for your target molecules using ab initio and Density Functional Theory (DFT) calculations in Gaussian, ORCA, or a comparable platform. I will provide validated, well-commented input files; optimized geometries; convergence and frequency checks; and clearly organized results for reaction energies, charge distributions, and spectroscopic properties. All key data will be parsed into CSV or Excel format, accompanied by a concise methods report covering functional and basis-set selection, convergence criteria, assumptions, and any noteworthy trends or anomalies. I am also comfortable with excited-state calculations, including Time-Dependent DFT (TD-DFT), and can automate calculation setup, monitoring, and result extraction using Python notebooks. I can complete the first batch within your two-week timeframe and deliver manuscript-ready, traceable results. Best regards, Damian

@rana335

Hello! I’m an AI video creator, graphic designer, and content writer. I can create high-quality, engaging, and professional content according to your requirements. I’m creative, detail-oriented, and focused on delivering excellent results on time. I’m ready to start immediately and would love to work with you on this project.

@lipsap13

Hello, I am interested in supporting your computational quantum chemistry project by building a structured and reproducible workflow for your molecular calculations. My expertise includes Python automation, scientific data processing, machine learning, validation, and technical reporting. I can prepare and organize Gaussian or ORCA input files according to your chosen computational protocol, automate output parsing, perform convergence checks, and deliver clean CSV/Excel tables for manuscript use. I can support: • Geometry optimization and calculation tracking • Extraction of reaction energies, charges, frequencies, and spectroscopic properties • Automated detection of failed or unconverged calculations • Python notebooks for reproducible parsing and analysis • Structured input, output, CSV, and Excel files • A concise methods report and summary of important trends or anomalies I want to be transparent that my strongest expertise is in Python-based scientific workflow automation and data analysis. For advanced quantum-chemistry decisions, I would follow your preferred functional, basis set, solvent model, and published methodology. I can begin with one representative molecule to validate the workflow before processing the full batch. Please share the number of molecules, target properties, preferred software, computational settings, and available resources. I am available for the proposed two-week timeline. Best regards, Lipsa Priyadarsinee

@yanezn

I have extensive experience conducting ab-initio and DFT calculations using Gaussian and ORCA, directly aligning with your quantum chemistry computational needs. My background includes optimizing molecular geometries and extracting reaction energies and spectroscopic data with rigorous attention to reproducibility. I focus on creating clean, well-documented input files and clear summaries that integrate seamlessly into manuscripts. My approach ensures convergence criteria are met and results are organized for easy analysis. Do you already have a preferred workflow automation setup, or should I include Python notebooks for this project? Happy to review your designs and discuss Phase 1 execution.

@muhammadayan1237

I’m new to freelancing, but I’m hardworking, reliable, and willing to learn. I will follow your requirements carefully and complete the project on time with my best effort.

@joeyb05

Not happy with the final result? Don’t pay. Your satisfaction comes first. I recently helped a client turn their idea into a clean, professional, and user-friendly solution, and I’d love to do the same for you. With extensive experience in quantum chemistry, I can efficiently run ab-initio and DFT calculations using Gaussian or ORCA. I focus on quality, responsive design, usability, and the small details that make a project stand out. I will ensure that all input files are well-commented and that the results are clearly presented in CSV format for easy integration into your manuscript. I’m also comfortable handling excited-state calculations and can automate workflows with Python notebooks, providing added value to your project. I’m happy to make adjustments until you’re completely satisfied. Send me a message and let’s discuss your project. Regards, Joey