PhD position in Computational Sciences within the national Data-Driven Life Sciences program
1 week ago
Project description
and tasksThis project addresses a fundamental topic in evolution concerning how and why microbes interact in the ways they do. We know that microbes have many possible options, or strategies, regarding what resources they consume to grow. Depending on these choices, pairs of microbes may either compete or cooperate. What actually happens depends on the ability of microbes to correctly assess the situation, i.e. solve a type of inference problem. Yet, little is known about the difficulty of this inference problem or what heuristics organisms might evolve.
This research project is a collaboration between Eric Libby and Laura Carroll. It involves using machine learning techniques to infer the mechanisms by which microbes make decisions, bioinformatic techniques to compare these mechanisms to empirical data, and game theory and modeling approaches to improve our understanding. The project has many exciting directions and opportunities for different quantitative tools and approaches.
Qualifications
The doctoral student will be admitted to study the third-cycle subject, Computational Science and Engineering (CSE), specialising in mathematics.
To be admitted for studies at third-cycle level the applicant is required to have completed a second-cycle level degree or completed course requirements of at least 240 ECTS credits, of which at least 60 ECTS credits are at second-cycle level, or have an equivalent education from overseas or equivalent qualifications. To fulfil the specific entry requirements to be admitted for studies at third-cycle level in CSE, the applicant is required to have completed at least 90 ECTS credits in CSE courses, of which at least 30 ECTS credits shall have been acquired at second-cycle level. CSE courses refer to courses with major quantitative, statistical, or computing science elements, such as courses in computing science, mathematics, and mathematical statistics, as well as relevant courses in biology, ecology, physics, and chemistry. Applicants who, in some other system either within Sweden or abroad, have acquired largely equivalent skills are also eligible.
Candidates need to be highly skilled in both oral and written communication in English, and must also be able to work independently as well as part of an interdisciplinary collaborative team.
Candidates must be proficient in at least one relevant programming language, e.g., Python, Rust, R, Julia, Matlab, C++, etc. A good background in mathematics, modeling, computer science, and/or programming is qualifying. Interest in and knowledge of evolutionary biology, microbiology, and molecular biology are desirable but not necessary, as well as interest in and knowledge of machine learning, bioinformatics, and data processing.
The PhD student is expected to play an active role in developing this doctoral project and the department. In addition, the PhD student is expected to have a scientific, structured, flexible, and result-oriented approach to their work.
The assessment of applicants is based on their qualifications and ability to benefit from the doctoral study they will receive.
About the employment
The position is intended to result in a doctoral degree. The main task of doctoral students is to pursue their third-cycle studies, including active participation in research and third-cycle courses. The duties may include teaching or other departmental work, although duties of this kind may not comprise more than 20% of a full-time post. The employment is for a fixed term of four years full-time or up to five years when teaching part-time. Salary is set according to the salary ladder for PhD positions at Umeå University. Employment commences fall 2024 or by agreement.
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