JMLab

Data Scientist

https://talent.gravityer.com/jmlab

TIFRH

India

Key Strengths

Extensive experience with Python for scientific computing and data analysis, as evidenced by numerous personal projects.
Strong background in applying machine learning and deep learning techniques to biological data (e.g., VAEs for protein-ligand interactions, GPT models for protein sequences, DDPM for conformational ensembles).
Demonstrated ability to work with complex biological simulation data (e.g., Gromacs, E. coli chromosome simulations).
Experience with Jupyter Notebooks for reproducible research and analysis.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are highly specialized in bioinformatics, computational biology, and biophysics, indicating a strong passion for scientific research and data science applications in these domains. The current role as 'Data Scientist' at 'TIFRH' aligns with the target role. However, the lack of diversity in project domains outside of biological sciences might indicate a narrower scope of interest or experience, which could impact cultural fit in a broader data science context. The experience level is listed as 0, which contradicts the current full-time role, suggesting a potential data discrepancy or a very recent entry into the professional field.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback are available.

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Projects

PTM_prediction

May 7, 2026 – Present

A repository for predicting phosphorylation, acetylation and ubiquitination sites from LoRA finetuned-ESM2 models

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beta_annealed_VAE

September 11, 2025 – September 11, 2025

beta_annealed_VAE — GitHub repository

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compresstraj

September 11, 2025 – September 11, 2025

compresstraj — GitHub repository

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DDPM_conformational_ensemble

September 11, 2025 – September 17, 2025

DDPM_conformational_ensemble — GitHub repository

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Hi-C_ML_structure-dynamics

September 11, 2025 – September 11, 2025

Hi-C_ML_structure-dynamics — GitHub repository

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idpGPT

March 2, 2024 – May 21, 2025

GPT models of PLMs trained to generate novel protein sequences when supplied with a prompt

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Protein_Ligand_Variational_Autoencoder

January 18, 2024 – January 19, 2024

This GitHub repository hosts implementations of Variational Autoencoder (VAE) and Denoising Convolutional VAE specifically designed for exploring protein-ligand interactions.

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p_ash1_p_sic1

July 29, 2023 – July 29, 2023

Study on phosphorylation of ash1 and sic1

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CymA-simulations

July 3, 2023 – July 5, 2023

Gromacs input topology and parameter files for simulation of CymA transporter.

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ecoli_finer

January 26, 2023 – March 29, 2024

scripts and code for generating and simulating E. coli chromosome at 500 bp inside a cell with ribosomes being present as the cytoplasmic particles.

View Project

Key Strengths

Extensive experience with Python for scientific computing and data analysis, as evidenced by numerous personal projects.
Strong background in applying machine learning and deep learning techniques to biological data (e.g., VAEs for protein-ligand interactions, GPT models for protein sequences, DDPM for conformational ensembles).
Demonstrated ability to work with complex biological simulation data (e.g., Gromacs, E. coli chromosome simulations).
Experience with Jupyter Notebooks for reproducible research and analysis.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback are available.

JMLab

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit