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Scholars Program (SP)

Students will be exposed to and have “hands-on” experience with CureScience scientists to conduct original, innovative research projects specifically in computational biology, machine learning and artificial intelligence. In addition to conducting original research, students will have an opportunity to explore scientific careers



  • Experience utilizing a variety of computational tools for biomedical informatics.
  • Lectures on a number of topics related to the program including but not limited to:
    • Learning about biomedical data analysis
    • Work with experienced faculty
    • Work with a designated Mentor


On a limited basis, the training program is available for undergraduate and high-school students from diverse backgrounds. The course is limited to the first eligible 20 students. We encourage under-represented minority students.
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Topics & Timeline


  • Scientific Research
  • Biostatistics
  • Artificial Intelligence
  • Biology & Biochemistry
  • Molecular Modelling
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  • Curescience offers rolling program entry points.

Applications require the following:

  • A personal statement*

  • Your educational transcript (unofficial transcripts are acceptable)

  • A resume

  • At least one, and up to three personal references.


* A personal statement provides you with an opportunity to explain why you are interested in the summer internship opportunity. Use your best judgement on what to include, but the following are often helpful to include:

  • A brief description of your academic record, relevant classes, etc.

  • A summary of any opportunities you have already had for research related activities. If you have not had these opportunities yet. That is OK, too.

  • We strongly recommend a description of your academic and career goals, but more importantly how the internship could help you accomplish them.


Send your application packet to training [at]


Frequently Asked Questions (FAQs)

I do not have (or only have limited) clinical, biomedical, and/or informatics background. Am I still encouraged to apply?

Yes, all applicants are encouraged to apply. Our trainees come from a diverse pool, some of whom have no formal clinical, biomedical, and/or informatics training/experiences.


Will there be an opportunity to work as intern after the training program?

Yes, exceptional candidates will be given an opportunity to work with our scientists over a period of time with a stipend. However, this requires a case-by-case evaluation.

I cannot fully attend the program. Would this still be okay?

Unfortunately, we would expect our trainees to fully attend the program. This is because we would like to make sure our trainees have enough time for a more complete research experience, and we have a structured program (including lectures, and final presentation conference) that we would like every trainee to attend.


Are there resources for travel to San Diego or housing in San Diego?

This program is primarily an online study program, so in most cases you would not need to visit San Diego.


Do I need to have anything to bring to the internship?

We recommend you have your personal laptop/computing device.

What is the cost for the training program?

An initial one time fee of $2500. Financial considerations will be given as required. 

I have more questions?

Reach us: training [at]




  1. MANDATORY: Scientific Research

    • Stages of Scientific Research

    • Methods of Scientific Research

      • Methods Flowcharts

      • Useful Tools for Scientific Research

    • Important Software for Scientific Research in Bioinformatics​​

    • How to Write a Scientific Paper

      • Structure of Scientific Paper

      • References

      • Plagiarism Detection

  2. MANDATORY: TBD-Biostatistics for Research

    • Research Planning (Research question, Hypothesis definition, Sampling, Experimental design, Data collection)

    • Analysis and Data Interpretation

      • Descriptive Tools (Frequency tables, Working with Excel, Line graph, Bar chart, Histograms, Scatter plot, Mean, Median, Mode, Box plot, Correlation coefficients, Pearson correlation coefficient, Confusion matrices, ROC curve)

      • Inferential Statistics (Hypotheses testing, Confidence intervals

    • Statistical Considerations (Power and statistical error, p-value, Multiple testing, Mis-specification and robustness checks, Model selection criteria)

    • Developments and Big Data (Use in high-throughput data, Bioinformatics advances in databases, data mining, and biological interpretation, Use of computationally intensive methods)

    • Applications

      • Systems biology for gene network inference or pathways analysis.

      • Basic Machine-Learning

    • Biomedical Informatics Tools

    • Statistics in Artificial Intelligence for Biology and Medicine. (Population and sampling, Types of data, Central tendency measures, Measures of shape and variance, Different types of distributions, Central limit theorem, Hypothesis testing

  3. Artificial Intelligence

    • AI: Definition, Types, Examples, and History. Taxonomy.

    • Supervised Machine Learning

    • Unsupervised Machine Learning

    • Semi-Supervised Machine Learning

    • Reinforcement Machine Learning

    • Learning-to-Learn Machine Learning

    • Deep-Learning

    • Data Mining for Scientific Discovery

    • Descriptors

    • The AI Approach to Diagnosing and Curing Disease

  4. Biology

    • OPTIONAL: Taxonomy

    • OPTIONAL: Microbiota and Microbiome

    • OPTIONAL: Phages

    • TBD- OPTIONAL: Virome

    • Fungi

  5. Biochemistry

    • Basics

      • Organic Nomenclature

      • Chemical Bonds (especially, Hydrogen Bonds)

      • Chemical Compounds of Living Systems

      • Functional Groups (Definition. hydroxyl, methyl, carbonyl, carboxyl, amino, phosphate, and sulfhydryl, etc.

    • Structure and Function of Important Biomolecules

      • Carbohydrates, Lipids, Nucleic Acids, and Proteins—Review

      • DNA and RNA

        • Nucleic Acids

      • Proteins

        • What Is a Protein?

        • Amino Acids

      • Advanced Glycation End Products

      • Signaling Pathways​

  6. Molecular Modeling

    • Pharmacophore Design

    • Homology Modeling of Proteins

    • Biomolecules Docking


2022/23 Timeline

Nov 10 2022: Application Period opens

Nov 2022: Interviews of applicants; Notification of acceptance or waitlist status

Jan 01, 2023: Program begins

May 25, 2023: Program concludes

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