AI Senior Project Manager - ML Lecturer - Physicist

Leading AI for biomolecular discovery.

I lead and build machine learning systems for computational drug discovery, protein-ligand interaction prediction, genomic sequence classification, and data-intensive scientific workflows.

Download CV Contact me Google Scholar GitHub LinkedIn
Current role
AI Senior Project Manager at Nostrum Biodiscovery
Teaching
MSc Machine Learning Lecturer at UPC
Base
Barcelona, Spain
Portrait of Manel Gil Sorribes

Working where AI leadership, molecular data, biology, and deployable research software meet.

About

A research engineer with a physicist's instinct for models.

I am an AI Senior Project Manager with expertise in transformers, model fine-tuning, and generative AI. At Nostrum Biodiscovery, I manage, develop, and optimize deep learning models for computational drug discovery, coordinating AI engineers, scientists, stakeholders, and client-facing technical communication.

My background combines physics, intelligent interactive systems, genomics research, production data engineering, and teaching machine learning labs in UPC's Master in Data Science. That mix helps me move from scientific question to data pipeline, model architecture, evaluation, communication, and practical delivery.

Experience

Leading applied AI across research, delivery, and teaching.

Dec 2025 - Present Nostrum Biodiscovery

AI Senior Project Manager

  • Leading AI and applied science projects in computational drug discovery.
  • Managing cross-functional teams of AI engineers, scientists, and stakeholders to deliver production-ready solutions.
  • Acting as the point of contact with clients, overseeing technical communication, progress reporting, and requirement alignment.
Jan 2024 - Dec 2025 Nostrum Biodiscovery

Artificial Intelligence Engineer

  • Developing and optimizing deep learning models for protein-ligand interaction prediction.
  • Researching transformer and generative AI techniques to improve model performance.
Feb 2026 - Present Universitat Politècnica de Catalunya

MSc Machine Learning Lecturer - Part-time

  • Teaching laboratory sessions for the Machine Learning course in the Master in Data Science.
  • Covering core machine learning techniques and hands-on practical implementations.
Apr 2023 - Jul 2023 European Joint Research Centre & UPF

AI & ML Intern - Genomics Research

  • Applied deep learning and machine learning techniques to genomic sequence classification.
  • Worked with large-scale biological datasets across preprocessing, feature extraction, and model optimization.
  • Developed and evaluated deep learning architectures for structured and unstructured sequence data.
Mar 2022 - Dec 2023 Capgemini

Business Intelligence Consultant - Data Engineer

  • Worked on data integration, transformation, and automation using PL/SQL, Informatica PowerCenter, and SAP.
Jun 2020 - Mar 2022 NTT Data

BI Consultant - Data Engineer

  • Integrated data from Oracle Data Warehouse to Salesforce using SQL and ETLs.
  • Enabled structured data processing and transformation for predictive modeling tasks.

Research Focus

AI systems for molecular and biological sequence data.

01

Computational drug discovery leadership

Applied AI project leadership across scientific requirements, model development, stakeholder alignment, and production delivery.

02

Protein-ligand interaction prediction

Deep learning workflows for modeling biomolecular interactions and supporting computational drug discovery.

03

Transformers and generative AI

Transformer-based modeling, LLM tooling, fine-tuning, and generative methods for scientific data problems.

04

Genomic sequence classification

Machine learning pipelines for biological sequence data, from preprocessing and feature extraction to model evaluation.

05

Machine learning education

Laboratory teaching for core ML techniques and practical implementations in a master's-level data science program.

Publications

Selected papers and conference work.

ICLR GEM and LMRL Workshops - 2025

Tensor-DTI: Enhancing Biomolecular Interaction Prediction with Contrastive Embedding Learning

Workshop paper presented at ICLR 2025 in Singapore.

arXiv PDF

Journal of Cheminformatics - 2026

Addressing Model Overcomplexity in Drug-Drug Interaction Prediction with Molecular Fingerprints

Open-access journal article on simple, interpretable molecular fingerprint baselines for DDI and DDA prediction.

Journal article DOI PubMed

ICLR LMRL and AI4NA Workshops - 2025

Character-level Tokenizations as Powerful Inductive Biases for RNA Foundational Models

Workshop paper presented at ICLR 2025 in Singapore.

arXiv PDF

Journal of Data-centric Machine Learning Research - 2025

Topobench: A framework for benchmarking topological deep learning

DMLR article introducing an open-source benchmarking framework for topological deep learning.

OpenReview PDF

ICML GRaM Workshop - 2024

ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain

Workshop paper from ICML 2024 in Vienna.

PMLR OpenReview

HCist Conference - 2023

Gut Microbiome Analysis for Health Assessment

Published and presented at the HCist Conference.

ScienceDirect

Selected Work

Professional work shaped around scientific usefulness.

Computational drug discovery

AI project leadership

Leading applied science projects, coordinating teams, aligning requirements, and communicating technical progress with clients.

Biomolecular interaction prediction

Protein-ligand modeling

Deep learning model development and optimization for predicting biomolecular interactions at Nostrum Biodiscovery.

Higher education

Machine learning labs

Part-time teaching for UPC's Master in Data Science, focused on core ML techniques and practical implementations.

Bioinformatics

Genomic sequence classification

Research internship work applying ML/DL methods to biological sequence datasets.

Technical Stack

Tools I use to bridge models, data, and delivery.

Machine Learning

PyTorch, TensorFlow, transformer models, generative AI, model fine-tuning

NLP & LLMs

BERT, GPT-3/4, Hugging Face Transformers, sequence modeling

Data Engineering

SQL, data preprocessing, ETL pipelines, PL/SQL, Informatica PowerCenter, SAP

Cloud & Software

GCP, AWS, Salesforce Sales Cloud, Informatica Cloud, Microsoft Office, LaTeX

Languages

Spanish and Catalan native, fluent English with B2 certificate, beginner Italian

Education

Academic foundation

Master in Intelligent Interactive Systems

Universitat Pompeu Fabra - 2023 - Barcelona, Spain

Machine Learning - Natural Language Processing - Deep Learning

Bachelor in Physics

Universitat de Barcelona - 2020 - Barcelona, Spain

Mention in theoretical physics

Certificates & Learning

Continued training

  • Google Cloud - Cloud Digital Leader
  • IICS - Cloud Data Integration Partner Bootcamp, Champion Certificate
  • Computer Vision Basics, University at Buffalo, Coursera
  • Bachelor thesis: Study of the Blume-Emery-Griffiths Phase Separation Model

Contact

Open to research conversations, AI/ML roles, and scientific collaborations.

The fastest way to reach me is email. You can also find my code and professional updates on GitHub and LinkedIn.

manelgiso@gmail.com Google Scholar LinkedIn GitHub Download CV