Associate Data Scientist | Personalized Medicine | Deep Tech Startup

Ilof Intelligent Lab On Fiber; Porto; Presencial; EUR 30 000 - 50 000; Tempo integral

Resumo da oferta

Ilof Intelligent Lab On Fiber is seeking an Associate Data Scientist in Porto to support innovative data science methods in personalized medicine. In this full-time onsite role, you will work with biomedical data, contributing to projects from analysis to validation. Ideal candidates hold a Master's or PhD, with 1–3 years of experience in handling high-dimensional data. Strong problem-solving and communication skills are essential, combined with a passion for data-driven research and development.

Qualificações

• 1–3 years of experience in academia or industry working on quantitative data problems.
• Experience in chemometric or multivariate analysis of spectroscopic data such as Raman, FTIR, or related high-dimensional signal data.
• Experience working with raw data alongside instrumentation.

Responsabilidades

• Support the data science workflow for specific projects, from problem framing to delivery.
• Analyse proprietary biomedical datasets to identify patterns, variability, and opportunities for improved performance.
• Help develop and apply statistical and machine learning methods for noisy, high-dimensional, and often small-sample data.
• Contribute to validation strategies, including uncertainty and robustness checks.
• Help improve preprocessing pipelines, signal quality, and acquisition protocols.

Conhecimentos

Hands-on Data Science

Experience with biomedical or spectroscopy data

Applied statistics

Predictive modelling

Experimental design

Data preprocessing

Feature engineering

Exploratory analysis

Problem-solving ability

Excellent communication skills

Formação académica

Master’s degree or PhD in Computer Science, Applied Math, Statistics, Physics, Engineering, or related field

Descrição da oferta de emprego

Associate Data Scientist | Personalized Medicine | Deep Tech Startup

• Full-time

At iLoF, you will help develop data science methods that extract reliable signals from biomedical and optical data. The role sits at the intersection of modelling, signal processing, and experimental science, with a focus on noisy, high-dimensional, and biologically complex datasets.

You will work with raw data generated on in-house instruments, helping improve signal quality, acquisition protocols, and hardware performance. You will also apply chemometric and multivariate methods to spectroscopic data such as Raman and FTIR, turning complex measurement signals into more reliable and interpretable insights.

You will work closely with experimentalists, hardware specialists, and product teams, directly influencing experimental design, data interpretation, and technology development — creating a tight feedback loop between theory and practice.

This is a high‑impact role in a growing team. We are looking for someone who combines strong technical foundations, scientific curiosity, and the ability to learn and execute well in a fast‑moving environment.

This is a fully onsite position, based at our Porto office

Responsibilities

• Support the data science workflow for specific projects, from problem framing to delivery.
• Analyse proprietary biomedical datasets to identify patterns, variability, and opportunities for improved performance.
• Help develop and apply statistical and machine learning methods for noisy, high‑dimensional, and often small‑sample data.
• Contribute to validation strategies, including uncertainty and robustness checks.
• Help improve preprocessing pipelines, signal quality, and acquisition protocols through work with raw data and instrumentation.
• Apply chemometric and multivariate analysis to spectroscopic data.
• Work cross‑functionally with experimental, hardware, and product teams.
• Communicate findings, trade‑offs, and recommendations clearly to technical and non‑technical stakeholders.
• Contribute to reusable analysis frameworks, documentation, and internal best practices.
• Stay up to date with developments in data science, computational modelling, and spectroscopy for clinical applications.
• Contribute to research publications, patents, and conference presentations where relevant.

Qualifications

• Hands‑on Data Scientist comfortable working in a fast‑paced startup environment and willing to grow by tackling challenging scientific problems.
• Experience with biomedical or spectroscopy data, or other high‑dimensional data where noise, batch effects, measurement artefacts, and instrument‑driven variation must be handled carefully.
• Developing skills in experimental design, validation strategy, and communicating uncertainty, trade‑offs, and limitations clearly.
• Experience working in interdisciplinary teams and collaborating with scientists and engineers across biology, hardware, and product.
• Master’s degree or PhD in Computer Science, Applied Math, Statistics, Physics, Engineering, or a related field. Exceptional candidates with relevant research or applied experience will also be considered.
• Around 1–3 years of experience in academia or industry working on quantitative data problems.
• Strong foundation in applied statistics, predictive modelling, and experimental design.
• Experience working with raw data alongside instrumentation, including optimisation of signal quality, acquisition protocols, or hardware performance.
• Experience in chemometric or multivariate analysis of spectroscopic data such as Raman, FTIR, or related high‑dimensional signal data.
• Strong data preprocessing, feature engineering, and exploratory analysis skills.
• Experience supporting validation strategies and interpreting model performance in ambiguous or noisy settings.
• Strong problem‑solving ability and comfort with incomplete, messy, or evolving data.
• Excellent written and verbal communication skills.
• Interest in mentoring and learning from senior colleagues is a plus.