Get up to date on the most advanced statistics, delving into R, biostatistics and analytical methodology with which to take your medical nutritional research to a high level"

Research on nutritional issues is not trivial, especially in a society increasingly involved in diets of all kinds, with conditions caused by poor nutrition or an unusual interest in a more careful diet. Nutritionists have a favorable field of action not only to address all these issues in a practical way, but also to investigate them through research that follows the nutritional trends of both the present and the future.

This is where the ability of nutrition professionals come into play to undertake a research project, a complex issue that requires multiple skills and knowledge that, in addition, must be updated to the latest scientific and technological precepts. For this reason, TECH has created this Professional master’s degree in Medical Research, aimed at providing an overall but at the same time exhaustive view of all the steps to be followed when undertaking a project of this nature.

Therefore,  nutritionists will learn different topics such as collaborative research, treatment of bibliographic and documentary sources or international funding calls, as well as the dissemination of results through reports, articles, conferences and even social networks. A whole appendix of contents that will give an improved, rigorous and current approach to the graduate's research projects.

In addition, the 100& online format of the program, without in-person classes or fixed schedules, allows total compatibility. It is the students who decide when, where and how to learn the entire teaching load, being able to distribute it at their own pace to adapt it to their work or personal responsibilities. Contents are available 24 hours a day from the virtual campus, accessible at any time from a computer, smartphone or device with Internet connection.

Invest in one of the research fields with the greatest current projection and obtain all the guarantees to undertake your own project in this Professional Master's Degree"

This Professional master’s degree in Medical Research contains the most complete and up-to-date scientific program on the market. Its most notable features are:

• 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

Learn how the R programming language can become an essential tool in your research, broadening your horizons in biostatistics, biomedical research and Data Mining"

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 course. This will be done with the help of an innovative system of interactive videos made by renowned experts. 

Acquire not only the best tools to collect and process data of all kinds, but also the knowledge to make high-level graphical representations"

All program contents can be downloaded directly to your computer or tablet of choice, providing you with a vital reference guide for your future nutritional research"

In order to ensure maximum efficiency when it comes to taking on the teaching load, TECH has made sure that all the contents of this program follow the Relearning methodology. This implies that the most important concepts and key topics on medical research are given repeatedly and progressively throughout the syllabus, resulting in a much more natural learning process. The savings in study hours that this implies, means that the Nutritionists can invest that time in delving into the subjects that generate greater interest, either through the several multimedia contents offered or the further readings provided.

In the virtual campus you will find videos in detail, interactive summaries, further readings and all kinds of audiovisual resources to make your academic experience much more rewarding"

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 Search Strategies 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 Evaluation 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: Symposia, Congresses, Dissemination to 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. Comics

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 Spin-Off Companies from a Research Project
10.10. Search for Investment Opportunities in Spin-Off Companies

The self-knowledge exercises and self-assessment tests will help you to reinforce your knowledge effectively in each module of the program"