Paul Spicher

Experience

Scientific Advisor Digital Health

Federal Office for Public Health

January 2025 — Present

Within the digital health team, I am primarily responsible for the following areas:

Data standards and interoperability
Digital health applications
Digital transformation of medication processes
Future technical infrastructure operated by the Swiss Confederation

Health Informatics Specialist | Data Scientist

Swiss Tropical and Publich Health Institute

August 2023 — December 2024

Digital Health Unit is a consulting-oriented team focusing on resource-constrained contexts.

Development and implementation of Clinical Decision Support Algorithms for paediatric consultations in Libya, Somalia and Nigeria.
Data analysis and management for the Dynamic clinical study, which aims to assess the ability of CDSS to reduce unnecessary antibiotic prescribing and improve clinical outcomes in paediatric patients in rural areas of Rwanda and Tanzania.
Strategic assessment of the positioning of CDSSs in a constantly changing technological and regulatory environment.

Project Associate

Swiss Institute of Bioinformatics

June 2022 — December 2022

Graph representation learning and RDF DB management on a drug discovery project.

Designed graph representation learning models to predict different biological activities from a large graph of LC-MS/MS data and other information related to a set of plant extracts.
Implemented the algorithms as pipelines that are easy to use for both bioinformaticians and less computer literate scientists.
Collaborated with teams of bioinformaticians, biologists and chemists to integrate the predictions of the models into the research of the partner laboratories.

Analyst - Medical Office

Réseau Hospitalier Neuchâtelois

June — August 2021

Exploratory projet on Electronic Health Record and Medical Information System data.

Review of state-of-the-art machine learning literature and identification of promising applications for the hospital
Implementation of two state-of-the-art supervised algorithms to concrete medical problems
Assessment of opportunities and challenges associated with the implementation of machine learning algorithms in the Medical Information System of the hospital

Staff Officer - Hospital Battalion 75 (CORONA 20)

Swiss Armed Forces

March — May 2020

Assistance service of the Hospital Battalion 75 to the cantonal health services in the fight against coronavirus in Switzerland.

Participation in the planning of personnel and material support for hospitals in the cantons Appenzell (Ausser- und Innerrhoden), Glarus, Schaffhausen, St. Gallen, Thurgau and Zürich
Advice to the battalion commander
Participation in the organisation and conduct of the daily business of the battalion (approx. 600 people)

Education

MSc Health Data Science

LSE • 2021 — 2022

Joint programme of the departments of Statistics and Health Policy designed to equip data scientists with statistical and computational methods specifically applicable to the healthcare, pharmaceutical and medical technology.

Awarded with Distinction
Societies: Data Science, Energy

MSc Epidemiology

LSHTM • 2023 — Present

MSc programme designed to be followed in parallel with a full-time job.
This programme equips students with the knowledge and statistical skills to make valuable contributions to medical research as well as public health in low-, middle- and high-income countries. Epidemiological methods underpin clinical medical research, public health practice and health care evaluation to investigate the causes of disease and to evaluate interventions to prevent or control disease.

BA HSG, Major in Economics

HSG • 2017 — 2021

1st year (assessment): Management, Business law and Economics
From 2d year: Major in Economics with specialization in Data Analytics and Data Handling
Societies: Data Science and Technology Club

Certificate in Medical Software and Medical Artificial Intelligence

Yale • 2024

Certificate followed in parallel with my full-time position at SwissTPH.
Focus on the technical and regulatory aspects of using rule-based software or software integrating ML models as medical devices.

Certificate in Applied Data Science - Machine Learning

EPFL • July 2019 — February 2020

Certificate obtained in parallel with my undergraduate degree. Focus on technical perspective:

15 ECTS in machine learning courses covering a wide range of classic models: KNN, Logistic regression, SVM, Random forest, Fully connected neural network, Convnet, ect.
Programming skills: Data handling and analysis with python
Application to a concrete problem in the field of image recognition (see projects)

Certificate in Data Science Fundamentals

HSG • 2018 — 2021

Certificate obtained in parallel with my undergraduate degree. Focus on decision maker’s perspective:

Ability to identify the potential of creating business and societal value out of data
Ability to communicate and work with “technical” and legal experts in a proactive and solution-oriented manner
Ability to explain the strengths or weaknesses of proposed solutions to those members of the management less well versed in technical matters
Technical perspective: Data handling and statistical modelling in R, application to a concrete business problem (see projects)