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Internship Computational Material Science Jobs in Indiana

Emphasizes mathematical rigor in chemical reasoning and connects physical chemistry to materials science, nanotechnology, and computational chemistry applications. * Curriculum Awareness & Adaptive ...

Emphasizes mathematical rigor in chemical reasoning and connects physical chemistry to materials science, nanotechnology, and computational chemistry applications. * Curriculum Awareness & Adaptive ...

Emphasizes mathematical rigor in chemical reasoning and connects physical chemistry to materials science, nanotechnology, and computational chemistry applications. * Curriculum Awareness & Adaptive ...

Emphasizes mathematical rigor in chemical reasoning and connects physical chemistry to materials science, nanotechnology, and computational chemistry applications. * Curriculum Awareness & Adaptive ...

Senior Mechanical Engineer

Crane, IN · On-site

$104K - $137K/yr

Familiarity with Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) tools ... material science, manufacturing, and hypersonic technologies-helping solve some of the nation ...

Senior Mechanical Engineer

Crane, IN

$104K - $137K/yr

Familiarity with Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) tools ... material science, manufacturing, and hypersonic technologies-helping solve some of the nation ...

Senior Mechanical Engineer

Crane, IN · On-site

$104K - $137K/yr

Familiarity with Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) tools ... material science, manufacturing, and hypersonic technologies--helping solve some of the nation ...

Bachelor's degree in Metallurgy, Material Science and Engineering * Ability to function in a Team environment Extra's * Internship experience in metal industry and/or Quality Systems. * Internship ...

Bachelor's degree in Metallurgical Engineering, Material Science or Chemical Engineering. * Working ... One internship at steel facility, industrial, or related environment. * Demonstrated success in ...

Showing results 41-60

Internship Computational Material Science information

What is an internship in computational material science?

An internship in computational material science is a temporary position, often for students or recent graduates, where participants work with experts to apply computer modeling and simulations to study materials at the atomic or molecular level. Interns typically use specialized software to predict material properties, analyze data, and support ongoing research projects. These internships provide hands-on experience in both materials science and computational techniques, helping to prepare individuals for careers or further study in the field.

What types of projects and collaborations can I expect during an internship in computational material science?

As an intern in Computational Material Science, you will typically work on projects involving the simulation and modeling of materials using computational tools and software. These projects often require close collaboration with other interns, research scientists, and sometimes experimentalists to validate your computational results. You may contribute to ongoing research, assist in code development, analyze data, and present findings to the team. This environment encourages skill development in programming, data analysis, and scientific communication, while also providing valuable exposure to multidisciplinary teamwork.

What are the key skills and qualifications needed to thrive as an intern in computational material science, and why are they important?

To thrive as an intern in Computational Material Science, you generally need a strong foundation in materials science, physics, chemistry, and programming, often supported by coursework or experience in these areas. Familiarity with simulation software (such as VASP, LAMMPS, or Quantum ESPRESSO), coding languages like Python or MATLAB, and potentially basic knowledge of high-performance computing systems is typically required. Analytical thinking, attention to detail, and effective communication are valuable soft skills that help in interpreting results and collaborating with research teams. These skills and qualities are essential for conducting accurate simulations, solving complex research problems, and contributing meaningfully to scientific projects.

What are the most commonly searched types of Computational Material Science jobs in Indiana?

The most popular types of Computational Material Science jobs in Indiana are:

What cities in Indiana are hiring for Internship Computational Material Science jobs?

Cities in Indiana with the most Internship Computational Material Science job openings:

Post Doc Research Associate

Purdue University

West Lafayette, IN • On-site

Full-time

Re-posted 11 days ago


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Company rating: 7.5 out of 10

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Job description

Post Doc Research Associate
City: West Lafayette
Job Description:
Job Summary
Position Title: Postdoctoral Research Associate - Bioinformatics, Pharmacogenomics, and AI/Machine Learning
Job Description: A Postdoctoral Research Associate position is immediately available for a highly motivated, independent, and ambitious candidate in the Department of Pharmacy Practice at Purdue University College of Pharmacy (Indianapolis campus). This position offers extensive collaborative research opportunities with the Regenstrief Institute and Indiana University. The successful candidate will work closely with faculty, scientists, clinicians, informaticians, health professionals, and trainees across institutions to develop and apply computational methods for biomedical discovery and precision therapeutics.
This position is ideal for candidates seeking advanced training and leadership opportunities in bioinformatics, pharmacogenomics, artificial intelligence, machine learning, computational drug discovery, and precision medicine.
Research Area
The postdoctoral fellow will contribute to projects in one or more of the following areas:
• Bioinformatics and computational biology
• Multi-omics data integration and analysis
• Pharmacogenomics and computational drug discovery
• Pharmacogenomics and precision medicine
• AI and machine learning applications in biomedical research
• Deep learning and predictive modeling
• Natural language processing and large language models for biomedical data
• Drug response prediction and treatment optimization
• Biomedical knowledge graphs and network medicine
• Translational data science for therapeutic discovery
Primary Responsibilities:
The Postdoctoral Research Associate is expected to lead and contribute to independent and collaborative research projects, including but not limited to:
• Developing and applying bioinformatics, pharmacogenomics, AI, machine learning, and deep learning methods
• Analyzing and integrating large-scale biomedical datasets, including omics, pharmacogenomics, medication, drug database, ontology, knowledge graph, and clinical molecular data
• Building computational pipelines for drug discovery, drug response prediction, therapeutic target identification, and precision therapeutics
• Developing predictive models, knowledge graphs, NLP/LLM applications, and AI-enabled analytic frameworks
• Leading manuscript preparation and contributing to grant proposals and scientific dissemination
• Collaborating with multidisciplinary stakeholders, including clinicians, biomedical scientists, informaticians, and data scientists
Education
Ph.D. or equivalent degree in a related field, such as bioinformatics, biomedical informatics, computer science, computational biology, biostatistics, pharmacogenomics, biomedical engineering, health data science, or a related discipline
Experience
1. Demonstrated research experience in one or more of the following areas: bioinformatics; pharmacogenomics; artificial intelligence; machine learning or deep learning; pharmacogenomics; computational biology; drug discovery; network medicine; NLP/large language models; or precision medicine
2. Strong programming skills in Python, R, SQL, or related languages
3. Experience with omics data, pharmacogenomics data, drug databases, biomedical ontologies, knowledge graphs, or large-scale biomedical datasets is highly desirable
4. Strong written and oral communication skills, with evidence of scholarly productivity, including peer-reviewed publications or conference presentations
5. Ability to work effectively with diverse multidisciplinary teams, including clinicians, biomedical scientists, informaticians, and data scientists
Application Materials:
Interested applicants should submit the following:
1. Curriculum Vitae
2. Cover letter explaining research interests, relevant experience, and career goals
3. Contact information for 2-3 references
Internal candidates use this link https://careers.purdue.edu/job/Postdoctoral-Research-Associate/43347-en_US/?isInternalUser=true
External candidates use this link https://careers.purdue.edu/job/Post-Doc-Research-Associate/43347-en_US/

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