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Leaders in Pharmaceutical Business Intelligence (LPBI) Group

Funding, Deals & Partnerships: BIOLOGICS & MEDICAL DEVICES; BioMed e-Series; Medicine and Life Sciences Scientific Journal – http://PharmaceuticalIntelligence.com

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IS, IT, CS and Data Science Internship

IS, IT, CS and Data Science Internship


Employer Partner: Leaders in Pharmaceutical Business Intelligence (LPBI)

Career(s)

Computer Science, Information Systems, Data Science,

Information Technology, MIS, Information Science

Overview

LPBI Internships offer the following:

  • Affiliation with and mentorship by esteemed scientists and research graduate students.
  • Skills development in NLP, ML, AI applications to Medical Text and Drug Discovery
  • References/letter of recommendation
  • Description of accomplishments and goals achieved during the internship
  • Opportunity to contribute to publications
  • Exploration of opportunities in life sciences in the US
  • Opportunity to collaborate with professionals from various fields such as medicine and Natural Language Processing as well as with other interns.

Internship Description

IP asset class IV: Cloud-based Platforms and Portals.

  1. Composition of Methods: Formats for Curations, Formats for electronic Table Of Contents (eTOCs), Role definition for Editors and Experts, Authors, Writers.
  2. Template system for e-Proceedings
  3. Template system for Tweeting in real time at volume
  4. GUI Design to manage outside queries to the system (B2C)
  5. Design Recommendation Engine Response (RER):

Types of Students Desired

College students majoring in Computer Science, Information Systems, Data Science, Information Technology, MIS, Information Science

Masters Students will be given additional coding tasks

Structure/Schedule

  • Cohort with individual assignments
  • Summer and academic school year internships
  • 12 week minimum – flexible schedule
  • Zoom 1 times per week with supervisor,
  • Zoom multiple times during internship with LPBI mentors

Internship Project Work

Example: 

  • Design Recommendation Engine Response (RER)

A) Fetching top articles by views

B) If the article was published in a book, then the selected Article in the context of all articles in the same chapter in the book it was featured in will form the article collection for NLP performance.

C) If the article was not published in a book, then in the context of other articles in the same categories of research selected by the recommendation engine and ranked by views

D) Assign value if article was produced live in a Conference

E) Create a subset of articles for A, B, C, D and generate Summation for Views since date of Publication

F) Sort articles by Author’s Name and by Summation of Views per article category and by Author’s name

G) Per Author computer article length by # of Words times Views. Summation across all Authors

Skills Used/Gained

  • System design
  • Template design
  • Graphical User Interface Design
  • Data Classification and Indexing
  • Rule-based system design
  • Coding

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