Doktorand i molekylär biovetenskap

## Responsibilities - To work within a multidisciplinary and international research environment. - To receive training in quantitative proteomics, structural biology, computational biology, machine learning, data integration, and scientific communication. - To participate in national courses, seminars, and networking activities within data-driven life science as part of the DDLS research school. - To conduct research within the framework of a DDLS-funded project at the intersection of structural proteomics, protein biophysics, and machine learning. - To use and develop both computational and experimental methods. - To contribute to data-driven life science (DDLS) by applying data, computational methods, and artificial intelligence to study biological systems and processes at all levels. ## Requirements - Must have basic and special eligibility for doctoral education. - Documented knowledge in relevant areas such as molecular biology, biochemistry, proteomics, structural biology, bioinformatics, computational biology, machine learning, or related fields. - Analytical and creative thinking. - Scientific curiosity and motivation for interdisciplinary research. - Initiative and independence. - Ability to collaborate in an international and interdisciplinary research environment. - Good ability to express oneself in spoken and written English. - Strong interest in protein science, proteomics, structural biology, computational biology, or machine learning. - Solid background in molecular biology, biochemistry, bioinformatics, computational biology, data science, physics, chemistry, or related fields. - Motivation to work in an interdisciplinary project linking experimental biological data to computational modeling. - Programming skills in Python, R, or other relevant programming languages. - Interest in machine learning, statistical modeling, structural bioinformatics, or analysis of large-scale biological datasets. - Experience in proteomics, mass spectrometry, protein structure analysis, molecular dynamics, deep learning, or bioinformatics is meritorious but not required. Experience in analysis of other types of -omics data is also valuable. - Curiosity, analytical thinking, and willingness to learn new experimental and computational methods. - Strong interest in interdisciplinary research and the integration of experimental proteomics with data-driven modeling is essential. ## Nice to Have - Experience in analysis of other types of -omics data. - Experience in molecular dynamics, deep learning, or bioinformatics. - Experience in structural bioinformatics or statistical modeling. ## Benefits - A limited-term appointment as a doctoral student according to Chapter 5 of the Higher Education Ordinance (1993:100). - The appointment duration cannot exceed what corresponds to full-time doctoral education over four years. - The doctoral student primarily devotes themselves to their own doctoral education, but work with education, research, and administration may be included in limited scope (up to 20%). - A new appointment as a doctoral student is for a maximum of one year, and the appointment is renewed thereafter in maximum two-year increments. - A workplace free from discrimination and offering equal rights and opportunities for all. - Contact information provided by Dr. Ilaria Piazza, [email protected]. - Application via Stockholm University's recruitment system, including a personal letter, CV, and any required attachments. - Instructions for applicants available on the university's website: how to apply for a position. - Stockholm University contributes to the sustainable democratic society's development through knowledge, enlightenment, and truth-seeking.