This contract is part of the ABBOTT RA67 PROJECT, funded by the company ABBOTT NUTRITION.

IMDEA Food is part of the Network of Madrid Institutes for Advanced Studies (IMDEA), promoted by the Regional Government of Madrid with the aim of developing research that is both socially valuable and of international scientific excellence.

Within this framework, and as part of the Nutritional Control of the Epigenome Research Group, the project titled “RA67: Exploring the association between polyphenol intake (circulating levels) and outcomes related to muscle and metabolism in adults 50+ yrs” is being developed. A postdoctoral researcher is required for its implementation.

Ref.: PD2025-020-ABBOTT – Postdoctoral Researcher
Principal Investigator: Dr. Lidia Daimiel Ruiz
Research Group: Nutritional Control of the Epigenome
Research Program: Precision Nutrition in Obesity
Research Line: Nutrition and the Epigenome; Liver-Heart Axis; AI and Personalized Nutrition

       Job description/ Functions to be carried out:

The NUCONEP research group is looking to recruit a highly motivated researcher to join the research sub-line focused on the application of artificial intelligence (AI) and multi-omic analysis in personalized nutrition.

The selected candidate will actively participate in the RA67 project dedicated to the application of advanced machine learning analytical methods on clinical, molecular, and nutritional data to develop predictive models of individual response to diet. This line aims to advance the clinical practice of precision nutrition by designing personalized dietary strategies based on metabolic and epigenetic profiles.

Main responsibilities:

• Processing, integration, and analysis of multi-omic (transcriptomics, epigenomics, metabolomics), nutritional, and clinical data.

• Development and validation of machine learning models to predict metabolic responses to nutritional interventions.

• Collaboration in the design of clinical studies and the interpretation of results from a computational perspective.

• Participation in the writing of scientific publications and the dissemination of results at national and international conferences.

• Support in the development of digital tools (apps, dashboards) for the implementation of personalized nutritional recommendations.

(Please, see FULL CALL FOR APPLICATION)

I. Entry requirements:

Education requirements:

* Education Level (Undergraduate, Bachelor Degree, Master Degree, PhD): PhD in Nutrition, Biomedicine, Biology, Pharmacy, Medicine or Health Science

Research Field: Nutritional Biocomputing

II. Evaluation of merits:

Other Education to evaluate:

* Master in Nutrition*

Professional experience & expertise to evaluate:

* At least 3 years of postdoctoral experience in the field and a minimum of 8 years of experience in the scientific field, including the predoctoral period, demonstrable through publications and conference presentations in the field of nutrition and biocomputing.

* H-index greater than 10.

* At least 30 scientific publications in the field of nutritional biocomputing.

* Proven mobility through at least three years of professional experience in a center other than the one where the doctoral thesis was completed, in prestigious research institutions with lines of work related to precision nutrition.

* Participation in R&D&I activities:

· Participation in European and international research projects for a minimum of two years, as well as in competitive research projects focused (on omics sciences.

· Contracts with companies in biostatistics and/or bioinformatics positions; participation in national and international agreements related to the research area of the position.

· Involvement in healthcare activities as a nutritionist in the field of epidemiology, especially in cohorts with high scientific impact

Other merits to evaluate:

• Co-author of scientific conference communications, preferably at the international level.
• Advanced knowledge of statistical modeling applied to nutritional and pharmacological biocomputation, with demonstrated experience as a data analyst using STATA, R Studio, and Python:
• Expert-level proficiency in implementing complex statistical models, machine learning techniques, and advanced inference methods applied to high-dimensional datasets. Proven ability to develop predictive, automated, and reproducible solutions with a solid statistical foundation.
• High-level statistical modeling using conditional logistic regression (fixed effects), multinomial regression, probit models, mixed and nonlinear models with restricted cubic splines, as well as survival models (multivariate Cox, Survivor functions), including the calculation of incidence rates, incidence rate ratios, and time-person adjusted SMRs. Estimation of marginal effects, predictive margins, advanced confidence intervals (percentiles, bootstrap, delta method), and post-estimation contrasts (likelihood ratio tests).
• Rigorous calculation of sample size and statistical power for clinical trials in the field of nutrition.
• Supervised machine learning and automated learning: implementation of regularized models, quantile regression, generalized models, optimized decision trees, SVM, and KNN, among others. Robust validation using techniques such as k-fold, LOOCV, bootstrap, and class-specific ROC/AUC curves.
• Clustering and unsupervised learning: development of segmentation models using K-means, DBSCAN, agglomerative hierarchical clustering, and GMM. Application of clustering analysis combined with PCA and t-SNE for dimensionality reduction and high-dimensional cluster visualization. Use of unsupervised validation metrics.
• Analytical visualization and results communication: creation of advanced visualizations and customized statistical tables, prepared for scientific publications or technical reports.
• Data monitoring and quality control using programming languages (STATA, R, Python) in clinical trials related to nutritional epidemiology.
• Nutritional assessment and computational quantification of nutrient intake, especially polyphenols, proteins, and dietary amino acids, using programming languages (STATA, R, Python).
• Experience in the analysis of high-protein dietary patterns, as well as in the study of dietary proteins and amino acids.
• Experience in metabolomic and other omics analyses.
• Drafting and development of clinical trial protocols in the field of precision nutrition.
• Scientific writing and preparation of research proposals for national and international funding calls.
• Teaching experiencia in nutritional biocomputation: supervisión of master’s theses, coordination of acedemic programs, teaching in bioinformatics and biostatistics, and academic management.

Capabilities & Skills (to evaluate in the interview):

• Communication and leadership.
• Project management skills (research and teaching).
• Motivation.
• Ability to work in a team.
• Ability to learn independently.
• Time management and prioritization of tasks in research projects.
• Commitment.

The selection of candidates shall be carried out in accordance with the principles of equality, merit, ability and publicity, as well as objectivity, independence and professional rigour, respecting the confidentiality of the personal data of the participants, by means of a merit-based competition.

Once the deadline for the submission of applications has expired, and once the fulfilment of the requirements listed in the second base has been verified, the Selection Committee will proceed to assess the merits included in the curricula vitae related to the post and to select the candidates who best meet the established requirements, and will then open a second selection phase consisting of a personal interview.

The personal interview will consist of a face-to-face or videoconference interview which will focus solely on the merits put forward by the candidates in the competition phase and will be aimed at assessing the candidate's suitability for the post. The interview will last a maximum of 45 minutes.

Scale - selection criteria:

The evaluation process will be carried out according to the following criteria:

I. Additional training to be assessed: 0-30*.

II. Experience to be assessed: 0-30*.

III. Other merits to be assessed: 0-10*.

IV. Interview: 0-30

Type of contract:  employment contract for scientific-technical project activities (Article 23 bis of the Science Act), in accordance with current legislation, with a trial period as established by law.
Working hours: 15 hours per week, split schedule, Monday to Friday, from 9:00 AM to 12:00 PM.
Gross Annual Salary: Highly competitive remuneration based on the qualifications and experience of the candidate.
Duration: 24 months
Start date: Immediate.

Headquarter of the IMDEA Food Insitute, Madrid (SPAIN)