Intern Quantitative Science
Intern Quantitative Science
Posted on :
20-01-2025
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1 Vacancy
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Job Description
Job Title: Intern Quantitative Science
Job Location: Home KS 66438 USA
Job Location Type: Remote
Job Contract Type: Fulltime
Job Seniority Level: Internship
/PROJECT: This intern role will support the Quantitative Science AI team in researching and developing AI applications to improve the efficiency of clinical trials. We will explore multiple areas where generative AI can play an important role reducing timelines and efforts while increasing efficiency. Some of these areas include clinical trial database creation data review knowledge management and information extraction. Role Responsibilities: Intern Quantitative Science
Equal Opportunity Employer/Veterans/Disabled
An Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin or protected veteran status and will not be discriminated against on the basis of disability. In the U.S. the salary range for this position is $ 21 to $30 per hour which factors in various geographic regions. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region jobrelated knowledge skills and experience among other factors.
- Contribute to the development of AI applications in drug research and development.
- Prepare training data (documents) needed for model building or prompt engineering.
- Develop workflows and prompts in OpenAI services.
- Write Python code for various applications.
- Passionate about science collaboration and learning new techniques.
- Experience in AI and machine learning models.
- Strong oral and written communication skills.
- Proficient programming skills in Python for data analysis and data wrangling.
- Consistent detailoriented communicative and dedicated to doing a job well done.
- Proficiency in the use of Microsoft Office Suite of tools (Outlook Word Excel etc.)
- Proficient in Python programming.
- Experience in NLP and predictive modeling/extrapolation methodologies.
- Experience using LLM and prompt engineering.
- Master level degree candidate or a rising senior working towards a bachelor’s degree; in a quantitative discipline (e.g. computer science data science statistics or similar) or another scientific degree from accredited University.
- Must be available to work full time 40 hours a week.
- Must be currently enrolled as a fulltime student at an accredited U.S. based university or college and enrolled in the fall term after the completion of the internship OR have graduated within 1 year of the start of the program.
- Must be able to relocate if necessary and work at the designated site for the duration of the internship for onsite hybrid roles. Some positions will be open to remote interns but employee must be within United States borders.
- Paid hourly wage paid company holidays and sick time
- Apply skills and knowledge learned in the classroom to onthejob experiences
- Comprehensive valueadded project(s)
- Develop skills specific to your major.
- Opportunities for professional development by building relationships and learning about other parts of the business.
- Participate in company all hands meetings monthly community lunches
- Corporate office amenities such as: 24/7 onsite gym coffee truck snacks
- Access to Employee Resource Groups
Equal Opportunity Employer/Veterans/Disabled
An Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin or protected veteran status and will not be discriminated against on the basis of disability. In the U.S. the salary range for this position is $ 21 to $30 per hour which factors in various geographic regions. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region jobrelated knowledge skills and experience among other factors.
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Employment Type
Full Time
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