Applied AI Research Scientist

TN Switzerland; Neuenburg; Vor Ort; USD 80’000 - 120’000; Vollzeit

Zusammenfassung

An early-stage, venture-backed start-up is seeking an Applied AI Research Scientist to innovate in blood pressure monitoring technology. This role involves designing and optimizing AI models, collaborating with diverse teams, and addressing technical challenges. The company, which has made significant strides in medical technology, offers a unique opportunity to impact health outcomes globally. If you possess a strong background in machine learning and a passion for solving real-world problems, this position could be your next exciting challenge!

Qualifikationen

• 2+ years of industry experience applying Deep Learning techniques.
• Strong publication record in Machine Learning or AI.

Aufgaben

• Design and develop innovative AI models for blood pressure estimation.
• Collaborate with cross-functional teams to solve complex problems.

Kenntnisse

Deep Learning

Machine Learning

Python

Statistical Learning

Problem-Solving

Communication Skills

Ausbildung

M.Sc. or Ph.D. in Computer Science

M.Sc. or Ph.D. in Machine Learning

M.Sc. or Ph.D. in Mathematics

M.Sc. or Ph.D. in Electrical Engineering

Tools

PyTorch

Scikit-learn

TensorFlow

Jobbeschreibung

Social network you want to login/join with:

Applied AI Research Scientist, Neuchatel

Client:

Location:

Job Category:

Other

Job Reference:

981ad547b950

Job Views:

2

Posted:

17.04.2025

Expiry Date:

01.06.2025

Job Description:

Company overview

We are an early-stage, venture-backed start-up that has raised over $50M from top-tier investors in Europe and the United States. We have developed and brought to market the world’s first continuous blood pressure monitor. Our technology is based on 15 years of research by our founders at the prestigious Swiss Center for Electronics and Microtechnology (CSEM). Aktiia's solution has been validated through extensive clinical trials and received a CE Mark as a Class IIa medical device giving us commercial access to 43 countries worldwide.

High blood pressure is the world’s most common disease and causes 18M deaths/year. At Aktiia, we believe that our novel technology is the key to building the fundamental datasets for the next chapter of understanding and discovery in the field of blood pressure. To strengthen our team, we are looking for a:

APPLIED AI RESEARCH SCIENTIST

Responsibilities

• Design, develop, optimize, and document innovative AI models for blood pressure estimation from optical signals.
• Analyze model limitations and devise strategies to enhance performance, addressing key challenges.
• Collaborate and communicate effectively with cross-functional teams to solve complex technical problems.

Your profile

• M.Sc. or Ph.D. in Computer Science, Machine Learning, Mathematics, Electrical Engineering, or a relevant field.
• 2+ years of industry experience applying Deep Learning techniques.
• Experience in developing, fine-tuning, and evaluating neural network architectures on large-scale datasets.
• Strong publication record in Machine Learning or AI.
• Deep understanding of statistical learning, CNNs, and RNNs.
• Proficiency in Python and machine learning frameworks (e.g., PyTorch, Scikit-learn, TensorFlow, etc.).
• Creative and hands-on approach to problem-solving.
• Strong communication skills in English (both written and spoken).
• Motivated, proactive, and curious, with a structured, solution-oriented mindset; a team player eager to learn.
• Comfortable working in a multidisciplinary, multicultural, and diversity-oriented team.
• Experience in medical signal processing or time series analysis is a plus.
• Based in Switzerland, with a valid Swiss work permit.

Are you passionate about solving problems with visionaries and innovative approaches? In this case, you are ready to rock with the Aktiia team. We look forward to receiving your application by email.

Only fully documented applications (CV, diplomas) will be considered for the recruitment process. If you do not hear back from us within two weeks, your application has unfortunately not been successful for this role.