Diandra H.

Chemometric Analysis, ML for Chemistry, Analytical Chemistry

Innovative scientist with expertise in computational chemistry, organic synthesis, and machine learning, driving advancements in drug discovery and molecular design. Proven ability to develop and apply computational workflows, predictive modeling, and data-driven methods to optimize drug design and support pharmaceutical research. Experienced in collaborating with multidisciplinary teams to develop novel therapeutics, including Alzheimer's disease drug candidates. Skills: Programming & Data Analysis: Python, R, RDKit, PyTorch, TensorFlow, scikit-learn Molecular Modeling Software: Maestro, Rosetta, MOE, Avogadro, Jmol, Spartan Cloud & HPC: Google Cloud Platform (GCP), AWS, Linux HPC environments Cheminformatics: High-dimensional data analysis, Bayesian optimization, cheminformatics workflows Data Visualization & Collaboration Tools: Matplotlib, Seaborn, Git, MS Office Organic Synthesis: Reaction optimization, asymmetric synthesis, small molecule design Spectroscopy: NMR, UV-Vis, Fluorescence, CD, GC-MS, LC-MS, FTIR