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Publicerad 2024-04-26

Step into the nexus of bioinformatics and machine learning as a researcher focused on gene expression modelling for applications in generative synthetic biology. This role is not just another position; it's a chance to redefine boundaries in an emerging scientific domain. Working hand-in-hand with experimental scientists, you'll drive innovations and turn computational insights into actionable synthetic biology breakthroughs, i.e. all results will be tested in the lab to iterate over models and hypotheses effectively. If you're geared up for challenge, collaboration, and direct impact, this is your arena. The opportunity to independently project in the environment allows for scientific creativity and innovation while developing leadership skills through project management and teamwork provides personal growth and a chance to make a meaningful impact. Overall, this position offers a unique and rewarding experience for candidates looking to advance their careers in a dynamic and progressive scientific setting. Project description This position entails working as part of the group of Associate Professor Aleksej Zelezniak. The Zelezniak lab is an interdisciplinary research group operating at the forefront of scientific exploration, combining the power of machine learning (ML) and artificial intelligence (AI) with cutting-edge experimental biology techniques for studying molecular systems. A primary focus of the group is unravelling the fundamental principles of gene expression regulation to advance synthetic biology applications. As a researcher in this role, you will lead computational work using ML approaches with applications in synthetic biology. You will lead your given project involving the analysis of large datasets from high-throughput NGS assays and training large neural networks to design DNA and proteins for multiple applications as required by the project objectives. Information about the division and the department The Department of Life Sciences at Chalmers University of Technology is dedicated to harnessing the potential of biological systems and innovative technologies for the conversion of biomass into diverse applications such as foods, pharmaceuticals, materials, chemicals, and fuels. The Division of Systems and Synthetic Biology (Sysbio), as one of the four divisions within the department, offers a vibrant and collaborative research environment. With researchers from over 30 countries, the department embraces a truly international atmosphere, providing ample opportunities for networking, cultural exchange, and professional growth. Nurturing the careers of young researchers is a key objective, ensuring that you will receive the support and resources necessary to flourish in your scientific journey. In summary, the position within the Zelezniak group at the Chalmers University of Technology offers a remarkable chance to work on the cutting edge of scientific discovery, combining ML and AI with wet lab experimentation. Furthermore, being part of the Department of Life Sciences and the Sysbio division provides access to a highly international and supportive research community. Embark on this transformative journey, where your skills and passion will contribute to advancing the frontiers of generative synthetic biology. Major responsibilities As a bioinformatician specialising in gene expression, this position requires a deep understanding of theoretical and methodological aspects of NGS data modalities, e.g. ATAC-seq, RNA-seq, single cell analysis. Your expertise in NGS analysis will be essential. In addition, your experience in machine learning and interest in developing your skills in generative AI will find its best use cases. An integral part of your responsibilities will involve leading projects independently, requiring your commitment, self-discipline and planning skills. Furthermore, you will have an opportunity to contribute to other interdisciplinary projects at the intersection of machine learning and protein engineering, exploring innovative approaches and advancing the frontiers of both fields. Alongside your research activities, you can supervise master's students, supporting their development and nurturing your leadership skills. Your involvement in interdisciplinary research, combined with the opportunity to work with cutting-edge technologies and other researchers like yourself, will enable you to make significant contributions to the field while continuously expanding your leadership and teamwork expertise. Qualifications The ideal candidate for this position should possess a PhD in bioinformatics/computational biology, focusing on genomics/evolution/protein engineering. The candidate should demonstrate experience in working with ML projects. Programming experience in Python/R is essential, including data analysis. Working with high-performance computing GPU clusters is highly desirable. It would be advantageous if the candidate had participated in international projects in the past. To qualify for the position of postdoc, you must hold a doctoral degree awarded no more than three years prior to the application deadline (according to the current agreement with the Swedish Agency for Government Employers). Exceptions from the 3-year limit can be made for longer periods resulting from parental leave, sick leave or military service*. The position requires sound verbal and written communication skills in English. Swedish is not a requirement but Chalmers offers Swedish courses. You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research and education. * The date shown in your doctoral degree certificate is the date we use, as this is the date you have met all requirements for the doctoral degree. Contract terms This postdoc position is a full-time temporary employment for two years. For more information about what we offer and the application procedure, please visit Chalmers website. *** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***

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Omfattning Heltid
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