Thanks to this Master's Degree, you will update all your knowledge about medical and biomedical research to offer a service adapted to the digital paradigm"

Given the proliferation of diseases that have affected the world, medical science is faced with a largely unknown paradigm. In the face of this uncertainty, healthcare professionals can only respond with more thorough research, for which it will be imperative that agents have all the advanced knowledge in the development of their work. Without forgetting that science would not be useful without the comparison of studies and, above all, the dissemination of their findings.

During the course of this program, the medical professionals will be introduced to all the phases of scientific and health research, from the creation of working groups, through clinical trials and project financing, to the dissemination of the results, through reports, articles and specific memories. In addition, thanks to TECH Global University, the professionals will respond to the great personnel demand presented by the current clinical market. All this, so that the specialists incorporate the use of Big Data in their public and private service, being aware of the latest positive evidence in this field.

A 100% online Master's Degree that allows you to balance the study of this program with the development of your personal and professional life, without having to do without either of them. In addition, the Relearning methodology applied by TECH Global University makes students forget about long hours of memorization and assimilate the contents in a gradual and simple way. An academic learning that aims to provide students with a broad update of knowledge.

Stand out in an industry in constant change due to the incorporation of new technologies in the medical field"

This Master's Degree in Medical Research contains the most complete and up-to-date scientific program on the market. The most important features include:

• Case studies presented by experts in Health Sciences Research
• The graphic, schematic, and practical contents with which they are created, provide scientific and practical information on the disciplines that are essential for professional practice
• Practical exercises where the self-assessment process can be carried out to improve learning
• Its special emphasis on innovative methodologies
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments
• Content that is accessible from any fixed or portable device with an Internet connection

Obtain all the keys to graphical representations of data in health research and other analysis you carry out, so you can compare different methods with dissemination tools"

The program’s teaching staff includes professionals from the sector who contribute their work experience to this educational program, as well as renowned specialists from leading societies and prestigious universities.

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide immersive education programmed to learn in real situations.

This program is designed around Problem-Based Learning, whereby the professional must try to solve the different professional practice situations that arise during the academic year For this purpose, the student will be assisted by an innovative interactive video system created by renowned and experienced experts. 

Boost your career by developing research projects that meet the demands of today's health science paradigm"

Upgrade your skills in collaborative research and attend to the essential threads to start an optimal research work"

The content of this Master's Degree in Medical Research has been carefully developed by TECH Global University with the support of a team of doctors and experts in Medical Research. In addition, the TECH has applied numerous educational tools that dynamize the study to motivate professionals to investigate their discipline with the latest techniques. One of them is the Relearning methodology, which exempts students from long hours of memorization, allowing them to assimilate the syllabus in a simple and gradual manner. In addition, TECH Global University offers hours of audiovisual materials in different formats: video summaries, activities, self-tests, explanatory videos, etc. All this, so that, from the first module, the specialists become familiar with the scientific method to follow to carry out health research.

A structured syllabus so that you can update your knowledge of Data as you move into the labor market"

Module 1. The Scientific Method Applied to Health Research. Bibliographic Positioning of the Research  

1.1. Definition of the Question or Problem to be Solved
1.2. Bibliographic Positioning of the Question or Problem to be Solved

1.2.1. Information SearchStrategies and Keywords Pubmed and Other Repositories of Scientific Articles
1.2.2. Pubmed and Other Repositories of Scientific Articles

1.3. Treatment of Bibliographic Sources
1.4. Treatment of Documentary Sources
1.5. Advanced Bibliography Search
1.6. Generation of Reference Bases for Multiple Use
1.7. Bibliography Managers
1.8. Extraction of Metadata in Bibliographic Searches
1.9. Definition of the Scientific Methodology to be Followed

1.9.1. Selection of the Necessary Tools
1.9.2. Design of Positive and Negative Controls in an Investigation

1.10. Translational Projects and Clinical Trials: Similarities and Differences

Module 2. Generation of Working Groups: Collaborative Research

2.1. Definition of Working Groups
2.2. Formation of Multidisciplinary Teams
2.3. Optimal Distribution of Responsibilities
2.4. Leadership
2.5. Control of Activities Achievement
2.6. Hospital Research Teams

2.6.1. Clinical Research
2.6.2. Basic Research
2.6.3. Translational Research

2.7. Creation of Collaborative Networks for Health Research
2.8. New Spaces for Health Research

2.8.1. Thematic Networks

2.9. Networked Biomedical Research Centers
2.10. Biobanks of Samples: International Collaborative Research

Module 3. Generation of Research Projects

3.1. General Structure of a Project
3.2. Presentation of Background and Preliminary Data
3.3. Definition of the Hypothesis
3.4. Definition of General and Specific Objectives
3.5. Definition of the Type of Sample, Number and Variables to be Measured
3.6. Establishment of the Scientific Methodology
3.7. Exclusion/Inclusion Criteria in Projects with Human Samples
3.8. Establishment of the Specific Team: Balance and Expertise
3.9. Expectations: An Important Element that we Forget
3.10. Budget Generation: a fine Tuning Between the Needs and the Reality of the Call
3.11. Ethical Aspects

Module 4. The Clinical Trial in Health Research

4.1. Types of Clinical Trials (CT)

4.1.1. Clinical Trials Promoted by the Pharmaceutical Industry
4.1.2. Independent Clinical Trials
4.1.3. Drug Replacement

4.2. Phases of CE
4.3. Main Figures Involved in CE5
4.4. Generation of Protocols

4.4.1. Randomization and Masking
4.4.2. Non-Inferiority Studies

4.5. Ethical Aspects
4.6. Patient Information Sheet 
4.7. Informed Consent
4.8. Good Clinical Practice Criteria
4.9. Drug Research Ethics Committee
4.10. Search for Funding for Clinical Trials

4.10.1. Public. Main Spanish, European, Latin American and U.S. Agencies
4.10.2. Private. Main Pharmaceutical Companies

Module 5. Project Financing

5.1. Search for Financing Opportunities
5.2. How to Adjust a Project to the Format of a Call for Proposals?

5.2.1. Keys to Success
5.2.2. Positioning, Preparation and Writing

5.3. Public Calls for Proposals. Main European and American Agencies
5.4. Specific European Calls for Proposals

5.4.1. Horizon 2020 Projects
5.4.2. Human Resources Mobility
5.4.3. Madame Curie Program

5.5. Intercontinental collaboration Calls: Opportunities for International Interaction
5.6. Calls for Collaboration with the United States
5.7. Strategy for Participation in International Projects

5.7.1. How to Define a Strategy for Participation in International Consortia
5.7.2. Support and Assistance Structures

5.8. International Scientific Lobbying

5.8.1. Access and Networking

5.9. Private Calls for Proposals

5.9.1. Foundations and Funding Organizations for Health Research in Europe and the Americas
5.9.2.  Private Funding Calls for Proposals from U.S. Organizations

5.10. Securing the Loyalty of a Funding Source: Keys to Lasting Financial Support

Module 6. Statistics and R in Health Research

6.1. Biostatistics

6.1.1. Introduction to The Scientific Method
6.1.2. Population and Sample. Sampling Measures of Centralization
6.1.3. Discrete Distributions and Continuous Distributions
6.1.4. General Outline of Statistical Inference. Inference about a Normal Population Mean. Inference about a General Population Mean
6.1.5. Introduction to Nonparametric Inference

6.2. Introduction to R

6.2.1. Basic Features of the Program
6.2.2. Main Object Types
6.2.3. Simple Examples of Simulation and Statistical Inference
6.2.4. Graphs
6.2.5. Introduction to R Programming

6.3. Regression Methods with R 

6.3.1. Regression Models
6.3.2. Variable Selection
6.3.3. Model Diagnosis
6.3.4. Treatment of Outliers
6.3.5. Regression Analysis

6.4. Multivariate Analysis with R

6.4.1. Description of Multivariate Data
6.4.2. Multivariate Distributions
6.4.3. Dimension Reduction
6.4.4. Unsupervised Classification: Cluster Analysis
6.4.5. Supervised Classification: Discriminant Analysis

6.5. Regression Methods for Research with R

6.5.1. Generalized Linear Models (GLM): Poisson Regression and Negative Binomial Regression
6.5.2. Generalized Linear Models (GLM): Logistic and Binomial Regressions
6.5.3. Poisson and Negative Binomial Regression Inflated by Zeros
6.5.4. Local Fits and Generalized Additive Models (GAMs)
6.5.5. Generalized Mixed Models (GLMM) and Generalized Additive Mixed Models (GAMM)

6.6. Statistics Applied to Biomedical Research with R I

6.6.1. Basic Notions of R. Variables and Objects in R. Data handling. Files Graphs
6.6.2. Descriptive Statistics and Probability Functions
6.6.3. Programming and Functions in R
6.6.4. Contingency Table Analysis
6.6.5. Basic Inference with Continuous Variables

6.7. Statistics Applied to Biomedical Research with R II

6.7.1. Analysis of Variance
6.7.2. Correlation Analysis
6.7.3. Simple Linear Regression
6.7.4. Multiple Linear Regression
6.7.5. Logistic Regression

6.8. Statistics Applied to Biomedical Research with R III

6.8.1. Confounding Variables and Interactions
6.8.2. Construction of a Logistic Regression Model
6.8.3. Survival Analysis
6.8.4. Cox Regression
6.8.5. Predictive Models. ROC Curve Analysis

6.9. Statistical Data Mining Techniques with R I

6.9.1. Introduction. Data Mining. Supervised and Unsupervised Learning. Predictive Models. Classification and Regression
6.9.2. Descriptive Analysis. Data Pre-Processing
6.9.3. Principal Component Analysis (PCA)
6.9.4. Cluster Analysis. Hierarchical Methods. K-Means

6.10. Statistical Data Mining Techniques with R II

6.10.1. Model Assessment Measures. Predictive Ability Measures. ROC Curves
6.10.2. Models Assessment Techniques. Cross-Validation. Bootstrap Samples
6.10.3. Tree-Based Methods (CART)
6.10.4. Support Vector Machines (SVM)
6.10.5. Random Forest (RF) and Neural Networks (NN)

Module 7. Graphical Representations of Data in Health Research and Other Advanced Analysis

7.1. Types of Graphs
7.2. Survival Analysis
7.3. ROC Curves
7.4. Multivariate Analysis (Types of Multiple Regression)
7.5. Binary Regression Models
7.6. Massive Data Analysis 
7.7. Dimensionality Reduction Methods
7.8. Comparison of Methods: PCA, PPCA and KPCA
7.9. T-SNE (t-Distributed Stochastic Neighbor Embedding)
7.10. UMAP (Uniform Manifold Approximation and Projection)

Module 8. Dissemination of Results I, Reports, Memos and Scientific Articles

8.1. Generating a Scientific Report or Memory of a Project

8.1.1. Optimal Approach to the Discussion
8.1.2. Presentation of the Limitations

8.2. Generation of a Scientific Article: How to Write a “Paper on the ” Basis of the Data Obtained?

8.2.1. General Structure
8.2.2. Where does the Paper Go?

8.3. Where to Start?

8.3.1. Adequate Representation of the Results

8.4. The Introduction: The Mistake of Starting with this Section
8.5. The Discussion: The Cusp Moment
8.6. The Description of Materials and Methods: The Guaranteed Reproducibility
8.7. Choice of the Journal where the Paper is to be submitted

8.7.1. Choice Strategy
8.7.2. Priority List

8.8. Adaptation of the Manuscript to the Different Formats
8.9. The "Cover Letter": Concise Presentation of the Study to the Editor
8.10. How to Respond to Reviewers' Doubts? The Rebuttal Letter

Module 9. Dissemination of Results II, Symposiums, Congresses, Dissemination to the Society

9.1. Presentation of Results at Congresses and Symposia

9.1.1. How is a Poster Generated?
9.1.2. Data Representation
9.1.3. Focusing the Message

9.2. Short Communications

9.2.1. Data Representation for Short Communications
9.2.2. Focusing the Message

9.3. The Plenary Lecture: Notes on How to Keep the Attention of the Specialized Audience for More than 20 Minutes
9.4. Dissemination to the General Public

9.4.1. Need Vs. Opportunity
9.4.2. Use of References

9.5. Use of Social Networks for the Dissemination of Results
9.6. How to Adapt Scientific Data to the Popular Language?
9.7. Hints for Summarizing a Scientific Paper in a Few Characters

9.7.1. Instant Dissemination via Twitter

9.8. How to turn a Scientific Paper into a Popularization Material

9.8.1. Podcast 
9.8.2. YouTube Videos 
9.8.3. Tik Tok
9.8.4. Comic Book

9.9. Popular Literature

9.9.1. Columns
9.9.2. Books

Module 10. Protection and Transfer of Results

10.1. Protection of Results: General Aspects
10.2. Valorization of the Results of a Research Project
10.3. Patents: Pros and Cons
10.4. Other Forms of Protection of Results
10.5. Transfer of Results to Clinical Practice
10.6. Transfer of Results to Industry
10.7. The Technology Transfer Contract
10.8. Trade Secrets
10.9. Generation of Companies  Spin-Off from a Research Project
10.10. Search for Investment Opportunities in companies Spin-Off

A program designed for professionals like you, who seek to improve their performance in health research, applying scientific methods"