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Post-Master's/Postdoctoral Researcher position– in Bioinformatics, AI & Software Engineering (2-Year Interdisciplinary Role) - Job Opportunity at Universität Bern

Bern, Switzerland
Contract
Mid-level
Posted: June 9, 2025
On-site
CHF 65,000 - 85,000 per year (approximately USD 70,000 - 92,000), reflecting the premium for interdisciplinary expertise in AI/bioinformatics within the Swiss academic-industry collaboration framework, with potential for performance-based supplements given the commercial applications

Benefits

Access to cutting-edge computational infrastructure and biopharmaceutical datasets, providing researchers with enterprise-grade tools typically unavailable in traditional academic settings
Collaborative research environment spanning multiple prestigious institutions including University of Bern, Genedata, and HES-SO Valais-Wallis, offering unprecedented networking opportunities
Direct engagement with industry stakeholders in the biopharmaceutical sector, providing real-world application experience that bridges academic research with commercial innovation
Publication opportunities across high-impact venues in bioinformatics, software engineering, and AI domains, enhancing academic profile and career prospects
Interdisciplinary exposure combining AI/ML, software engineering, and bioinformatics, positioning researchers at the forefront of emerging biotechnology trends

Key Responsibilities

Lead the development of revolutionary AI/ML-driven analytical frameworks for biopharmaceutical data processing, directly impacting drug discovery and development timelines across the industry
Architect and implement scalable "Bioinformatics-as-a-Service" (BAAS) platforms that will transform how pharmaceutical companies approach data analysis workflows
Drive cross-institutional collaboration initiatives that establish new standards for academic-industry partnerships in computational biology and AI innovation
Translate complex research findings into commercially viable software solutions, bridging the critical gap between academic innovation and market-ready biotechnology products
Establish thought leadership through high-impact publications that will influence the direction of AI applications in biopharmaceutical research and development

Requirements

Education

Master's or PhD degree in Bioinformatics, Computer Science, Software Engineering, or a related field

Experience

Post-master's or postdoctoral level experience

Required Skills

Strong programming abilities (especially coding in R, Python, and/or similar languages) Experience with bioinformatics is desirable Understanding of bioinformatics workflows and data formats (or willingness to gain rapid familiarity) is desirable Familiarity with AI/ML techniques and software development practices Strong organizational, communication, and collaborative skills Proficiency in English (spoken and written) is required Experience with state-of-the-art mass spectrometry computational tools Experience in developing analytical pipelines or computational biology tools Knowledge of data engineering or DevOps pipeline tools Strong communication and teamwork skills in an interdisciplinary setting
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Sauge AI Market Intelligence

Industry Trends

The biopharmaceutical industry is experiencing a paradigm shift toward AI-driven drug discovery and development, with companies investing billions in computational biology platforms to accelerate research timelines and reduce development costs. This transformation is creating unprecedented demand for professionals who can bridge traditional bioinformatics with modern AI/ML methodologies. Bioinformatics-as-a-Service (BAAS) platforms are emerging as critical infrastructure for pharmaceutical companies, enabling smaller biotech firms to access enterprise-grade analytical capabilities without massive capital investments. This trend is democratizing drug discovery and creating new market opportunities for specialized service providers. The integration of real-time data processing and AI-enhanced system self-assessment in bioinformatics workflows represents a cutting-edge approach that addresses the industry's need for adaptive, intelligent analytical tools capable of handling the exponential growth in biological data generation. European pharmaceutical and biotechnology sectors are increasingly emphasizing interdisciplinary collaboration between academic institutions and industry partners, with Switzerland positioning itself as a global hub for computational biology innovation through initiatives like this BioAI4LCSM project.

Role Significance

The role involves leading a distributed team structure across three institutions, likely coordinating with 8-12 researchers, engineers, and industry professionals while maintaining direct reporting relationships with principal investigators at each participating organization
This position represents a high-impact mid-career role that combines the intellectual freedom of academic research with the practical constraints and opportunities of industry collaboration. The role holder will function as a bridge between theoretical innovation and commercial application, with significant autonomy in research direction while maintaining accountability to industry stakeholders and measurable outcomes.

Key Projects

Development of next-generation mass spectrometry data analysis platforms that incorporate machine learning algorithms for pattern recognition and anomaly detection in complex biological datasets Creation of automated workflow orchestration systems that can adapt to different pharmaceutical research contexts while maintaining regulatory compliance and data integrity standards Implementation of real-time bioinformatics processing pipelines capable of handling multi-omics datasets from clinical trials and preclinical research studies

Success Factors

Ability to effectively communicate complex technical concepts across disciplinary boundaries, particularly when presenting AI/ML innovations to bioinformatics specialists and explaining biological context to software engineers and data scientists Demonstrated capacity for rapid learning and adaptation, as the role requires quickly absorbing domain-specific knowledge in biopharmaceutical workflows while simultaneously staying current with rapidly evolving AI/ML methodologies Strong project management and stakeholder coordination skills, essential for managing expectations and deliverables across academic institutions with different cultures, timelines, and success metrics while meeting industry partner requirements Technical versatility and depth, particularly the ability to architect scalable software solutions that can transition from research prototypes to production-ready systems capable of handling enterprise-scale biopharmaceutical data

Market Demand

Very High - The convergence of AI, bioinformatics, and pharmaceutical applications represents one of the fastest-growing segments in biotechnology, with demand significantly outpacing the supply of qualified professionals who possess this specific interdisciplinary skill set

Important Skills

Critical Skills

Advanced programming proficiency in R and Python is absolutely essential as these languages form the backbone of modern bioinformatics workflows and AI/ML implementation in pharmaceutical research. The ability to write efficient, scalable code that can handle large-scale biological datasets is fundamental to success in this role. Deep understanding of AI/ML techniques, particularly as applied to biological and pharmaceutical data, is crucial for developing the adaptive, intelligent systems that represent the core innovation of this project. This includes knowledge of machine learning algorithms, neural networks, and their specific applications to biological pattern recognition. Strong interdisciplinary communication skills are critical for success, as the role requires effectively bridging the gap between software engineering concepts, bioinformatics methodologies, and pharmaceutical research requirements while coordinating across multiple institutional contexts.

Beneficial Skills

Experience with mass spectrometry computational tools provides significant advantages given the project's focus on biopharmaceutical applications, as mass spectrometry data analysis represents a major bottleneck in current pharmaceutical research workflows Knowledge of DevOps and data engineering practices becomes increasingly valuable as the project moves toward production-ready BAAS platforms, enabling the transition from research prototypes to scalable, enterprise-grade solutions Background in regulatory compliance and pharmaceutical data standards offers substantial benefits for ensuring that developed solutions can be adopted by industry partners while meeting stringent regulatory requirements for pharmaceutical research and development

Unique Aspects

This role offers rare direct access to proprietary biopharmaceutical datasets and computational infrastructure typically available only to senior researchers at major pharmaceutical companies, providing unprecedented learning and development opportunities
The position uniquely combines academic research freedom with commercial application requirements, allowing for both theoretical innovation and practical impact measurement in real-world pharmaceutical development contexts
The two-year structured timeline provides an intensive, focused experience that can significantly accelerate career development while producing tangible outcomes that enhance professional reputation across multiple domains
Direct collaboration with Genedata, a commercial leader in bioinformatics software, offers insider access to industry best practices and potential pathways to commercial biotechnology careers

Career Growth

2-4 years for transition to senior industry roles, 3-5 years for academic leadership positions, with accelerated progression possible given the high demand for interdisciplinary expertise in this rapidly expanding field

Potential Next Roles

Principal Scientist or Research Director positions at major pharmaceutical companies focusing on computational biology and AI-driven drug discovery platforms Founding or co-founding roles at biotechnology startups specializing in bioinformatics software solutions and AI applications in pharmaceutical research Senior academic positions such as Assistant Professor or Research Group Leader with a focus on computational biology and bioinformatics innovation Chief Technology Officer or VP of Data Science roles at biotech companies developing next-generation analytical platforms for pharmaceutical applications

Company Overview

Universität Bern

The University of Bern is a leading European research institution with particular strength in computational sciences and interdisciplinary collaboration, while this specific project involves partnership with Genedata, a Swiss-based leader in bioinformatics software solutions for pharmaceutical and biotechnology companies, and HES-SO Valais-Wallis, known for applied research in data analytics and algorithmic modeling.

This consortium represents a powerhouse combination of academic excellence and commercial expertise, positioning participants at the forefront of European biotechnology innovation with direct access to both cutting-edge research methodologies and market-validated commercial applications
Switzerland's role as a global pharmaceutical hub, home to major companies like Novartis and Roche, provides unique advantages for this position, including access to industry expertise, potential collaboration opportunities, and exposure to world-class biopharmaceutical research and development practices
The interdisciplinary nature of this role suggests a dynamic, collaborative environment that values both academic rigor and practical innovation, with emphasis on cross-cultural communication and the ability to work effectively across different institutional cultures and expectations
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