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Summer Scholars Program (SSP)

Under the guidance of CureScience scientists students will conduct

original, innovative research projects specifically in computational biology,

machine learning, and artificial intelligence. A weekly hour and a half lecture for the students will be conducted by the CureScience scientists. Students are expected to spend at least four hours a day working on an independent project. Students will also have an opportunity to explore scientific careers with CureScience scientists. 



  • 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.

To apply for the program, you must complete the following:

1.  Submit your application

2. Have one of your teachers or mentors submit the Teacher Recommendation form

Application forms will require the following:

  • A personal statement*

  • Your educational transcript (unofficial transcripts are acceptable)

  • A resume


* 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.


"I would recommend the program to anyone who is interested in learning more about computational biology. I enjoyed the fact that I got to do much of the project myself, which taught me various useful skills. I was trained in using DAVID to find pathway information and WEKA to trail ML models. I am currently working on a project where I am predicting the radiosensitivity of tumors using genetic biomarkers and machine learning."

Miles K.

High School Student

"I wanted to take a moment to express my heartfelt gratitude for inspiring my interest in computational biology through the opportunity given to work on a research project. As a result of the guidance and mentorship, I have developed a passion for this field and it has motivated me to undertake a project on using machine learning to repurpose FDA-approved drugs for the treatment of Diabetic Cardiomyopathy. I am thrilled to share with you that the project has been successful. At the Greater SD Science Fair, I received the Grand Award runner up and have also qualified for the California Science and Engineering Fair. This achievement would not have been possible without the foundational knowledge and skills I acquired through your guidance and support."

Vishnu A.



Igor Tsigelny
Valentina Kouznetsova

Igor Tsigelny, PhD


Computational Biology

Valentina Kouznetsova, PhD




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?

A one-time fee of $2500. Financial considerations will be given as required. 

I have more questions?

Reach us:




  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: 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


Summer 2023 Timeline

April 10, 2023: Application period opens

June 2, 2023: Application period closes

June 12, 2023: Program begins

August 18, 2023: Program concludes

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