Computational Chemistry/Chemin
招聘时间
即日起 至 2026-09-13
招聘单位
罗氏中国
所在地区
上海
工作地点
上海市/上海/浦东新区
学历要求
本科
实习时长
每周5天，每天3小时
职责描述
Computational Chemistry/Cheminfomatics Intern - AIDD
Qualifications & Required Skills:
● Education & Core Stack: Master or PhD candidate in Computational Chemistry, Cheminformatics, Molecular Modeling, Machine Learning, or a related discipline. Fluency in Python and proficiency with relevant toolkits.
● Specialized Expertise: Candidates should possess strong practical experience in AT LEAST ONE of the following two areas:
o Track A (Cheminformatics & Representation): Proficiency in generating, manipulating, and applying chemical representations, such as SMILES, Reaction SMARTS, or equivalent formats. Experience developing Python-based tools and workflows for molecular fragmentation tasks. A solid foundational understanding of organic chemistry and the drug discovery pipeline.
o Track B (Conformational Sampling & Quantum Chemistry): Experience with automated, high-throughput searches for low-energy conformers in conformational space. Experience of transition state search is preferred. Familiarity with testing Machine Learning Potentials (MLPs) and comparing the results against Density Functional Theory (DFT) calculations.
● Preferred Qualification (Highly Desired): Experience or empirical knowledge in structure-based generative modeling, specifically fragment-based molecule generation within protein binding pockets.
● Soft Skills: Good written and verbal communication skills in both Chinese and English.
Qualifications & Required Skills:
● Education & Core Stack: Master or PhD candidate in Computational Chemistry, Cheminformatics, Molecular Modeling, Machine Learning, or a related discipline. Fluency in Python and proficiency with relevant toolkits.
● Specialized Expertise: Candidates should possess strong practical experience in AT LEAST ONE of the following two areas:
o Track A (Cheminformatics & Representation): Proficiency in generating, manipulating, and applying chemical representations, such as SMILES, Reaction SMARTS, or equivalent formats. Experience developing Python-based tools and workflows for molecular fragmentation tasks. A solid foundational understanding of organic chemistry and the drug discovery pipeline.
o Track B (Conformational Sampling & Quantum Chemistry): Experience with automated, high-throughput searches for low-energy conformers in conformational space. Experience of transition state search is preferred. Familiarity with testing Machine Learning Potentials (MLPs) and comparing the results against Density Functional Theory (DFT) calculations.
● Preferred Qualification (Highly Desired): Experience or empirical knowledge in structure-based generative modeling, specifically fragment-based molecule generation within protein binding pockets.
● Soft Skills: Good written and verbal communication skills in both Chinese and English.
