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Internship Machine Learning Chemistry Jobs in Indiana

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Internship Machine Learning Chemistry information

What are some common challenges faced during a Machine Learning Chemistry internship, and how can interns overcome them?

Interns in Machine Learning Chemistry often encounter challenges such as bridging the gap between computational methods and chemical domain knowledge, working with complex and sometimes limited datasets, and adapting to rapidly evolving technologies. To overcome these hurdles, it's helpful to proactively seek mentorship from both data scientists and chemists within the team, dedicate time to learning domain-specific concepts, and regularly participate in team discussions to clarify project goals. Embracing a collaborative mindset and staying curious will also help interns effectively contribute and grow in this interdisciplinary environment.

What are the key skills and qualifications needed to thrive as an Internship Machine Learning Chemistry, and why are they important?

To thrive as an intern in Machine Learning Chemistry, you need a solid understanding of chemistry fundamentals and proficiency in programming languages such as Python, often supported by ongoing or completed coursework in chemistry, computer science, or related fields. Familiarity with machine learning libraries (e.g., scikit-learn, TensorFlow), cheminformatics tools (e.g., RDKit), and data analysis platforms is highly valued. Strong analytical thinking, problem-solving skills, and teamwork set standout candidates apart in collaborative research environments. These skills are important to effectively develop, implement, and interpret machine learning models that address complex chemical problems.

What is an Internship in Machine Learning Chemistry?

An Internship in Machine Learning Chemistry is a temporary, often academic or industry-based position where students or early-career professionals gain hands-on experience applying machine learning techniques to solve problems in chemistry. Interns may work on projects involving data analysis, molecular modeling, drug discovery, or material design using algorithms and computational tools. The internship provides practical exposure to interdisciplinary research, allowing interns to collaborate with chemists, data scientists, and engineers. It is an excellent opportunity to develop both technical and professional skills in a rapidly growing field.

What is the difference between Internship Machine Learning Chemistry vs Chemistry Research Intern?

AspectInternship Machine Learning ChemistryChemistry Research Intern
Required CredentialsBasic programming, chemistry knowledge, courseworkChemistry coursework, lab skills, basic research experience
Work EnvironmentData analysis, coding, computational toolsLaboratory experiments, chemical analysis
Industry UsageTech companies, research labs integrating ML and chemistryAcademic, industrial chemistry labs
Search & Comparison IntentUnderstanding roles combining ML and chemistry internshipsTraditional chemistry research internship details

Internship Machine Learning Chemistry focuses on applying machine learning techniques to chemistry problems, often involving coding and data analysis. In contrast, Chemistry Research Internships emphasize hands-on laboratory research in chemistry. Both roles require chemistry knowledge, but the former integrates computational skills, making it ideal for those interested in data-driven chemistry careers.

What are the most commonly searched types of Machine Learning Chemistry jobs in Indiana? The most popular types of Machine Learning Chemistry jobs in Indiana are:
What are popular job titles related to Internship Machine Learning Chemistry jobs in Indiana? For Internship Machine Learning Chemistry jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Internship Machine Learning Chemistry jobs in Indiana look for? The top searched job categories for Internship Machine Learning Chemistry jobs in Indiana are:
What cities in Indiana are hiring for Internship Machine Learning Chemistry jobs? Cities in Indiana with the most Internship Machine Learning Chemistry job openings:
Internship Machine Learning Chemistry jobs near you
Computational Chemistry/Toxicology Scientist

Computational Chemistry/Toxicology Scientist

Vish Consulting Services Inc

Zionsville, IN • On-site

Contractor

Posted 29 days ago

Job description

VCS is looking for a computational chemistry/Toxicology Scientist for one of our client

Job Title - Computational Chemistry/Toxicology Scientist

Job Location - Indianapolis, IN 46077

Contract- 12+ Months with possible extension

Shift- Day M-F 40 hrs./week

Pay- 57/Hr.

Description:
The client has an exciting and challenging opportunity in the Predictive Safety Center within Regulatory Science for a Computational Scientist Contractor with expertise in c/Bioinformatics. The individual will partner with a multidisciplinary team to design, develop, and implement machine learning models to predict safety profiles of chemicals to support the discovery, development and registration of novel crop protection products. This position is located in Indianapolis, IN, while strong candidates working remotely will be considered.
Responsibilities:

  • Develop and apply chemistry structure-based predictive models for assessing safety profiles of early-stage discovery molecules
  • Assess potential mechanisms of toxicity by assessing ligand-protein binding affinity using protein structure alignment, binding pocket evaluation, and molecular docking
  • Work collaboratively with internal and external cross-functional multidisciplinary teams, collaborators, and consultants to implement in silico models to meet business needs
  • Serve as a subject matter expert on in silico modelling for the team and other partners in R&D sub-functions
  • Present the development and application of cheminformatics/bioinformatics approaches and novel ML/DL models internally and externally including scientific conferences
  • Keep abreast of the latest scientific development in the areas of machine learning, cheminformatics, bioinformatics, and related fields and identify technologies to be applied internally
  • Analyze complex datasets using machine learning approaches and interpret results to improve data-driven decision-making processes

Qualifications:

  • Ph.D. degree in Cheminformatics, Computational Chemistry, Computational Biology, Bioinformatics, Toxicology, or a related field
  • 3+ years of experience in developing machine learning models and applying cheminformatics/bioinformatics and AI for structure-based drug design, toxicology assessment, mechanism prediction
  • Strong technical background in machine learning, deep learning, and statistical modeling with prior experience in applying these techniques to process, analyze and draw insights from complex datasets involving chemical compound structures and toxicity endpoints
  • Demonstrated programming proficiency in Python and experience in utilizing machine learning libraries
  • Demonstrated in-depth knowledge in toxicology, chemistry, chemical structure, QSAR, protein structure
  • Knowledge in omics analysis and systems biology is a plus
  • Demonstrated teamwork and project leadership skills to manage multiple projects on different timelines for stakeholders across the business
  • Excellent communication and presentation skills to different stakeholder audiences

Thank You!

Bhanendra S Singh
Vish Consulting Services(VCS)
Bhanendra @vishusa.com