Doctoral student in AI-driven phylogenetic analysis of cancer evolution Full-time

Doctoral Student In Ai And Machine Learning For Analysis Of Single-Cell Cancer Data

KTH Royal Institute of Technology, School of Electrical Engineering and Computer Science

Project Description

Third-cycle subject: Computer Science

The project focuses on developing probabilistic and AI-enhanced Bayesian methods for analyzing tumor DNA as well as circulating tumor DNA (ctDNA). The aim is to determine whether ctDNA signals can be explained by the primary tumor or whether they indicate metastasis. The project combines phylogenetic models with single-cell data and longitudinal blood samples.

The work includes developing new inference methods based on deep learning, generative AI, and variational inference.

The project is conducted in close collaboration between KTH and Karolinska Institutet, with access to unique data from international cancer studies. We are seeking candidates with a strong background in computer science, mathematics, machine learning, or computational biology. Funding is secured through DDLS research funding.

Supervision: Jens Lagergren is proposed to supervise the doctoral student. Decisions are made on admission

Admission Requirements

To be admitted to postgraduate education (Chapter 7, 39 § Swedish Higher Education Ordinance), the applicant must have basic eligibility in accordance with either of the following:

• passed a second cycle degree (for example a master's degree), or
• completed course requirements of at least 240 higher education credits, of which at least 60 second-cycle higher education credits, or
• acquired, in some other way within or outside the country, substantially equivalent knowledge
• A Master's degree (or equivalent) in computer science, mathematics, statistics, bioinformatics, or a related field.
• Strong competence in programming and quantitative methods is required.

In addition to the above, there is also a mandatory requirement for English equivalent to English B/6.

Selection

In order to succeed as a doctoral student at KTH you need to be goal oriented and persevering in your work. During the selection process, candidates will be assessed upon their ability to:

• independently pursue his or her work
• collaborate with others,
• have a professional approach and
• analyze and work with complex issues.
• Experience in AI, machine learning, Bayesian inference, mathematics, programming, or phylogenetic models is considered meritorious.

After the qualification requirements, great emphasis will be placed on personal skills.

Target Degree: Doctoral Degree

Information Regarding Admission And Employment

Only those admitted to postgraduate education may be employed as a doctoral student. The total length of employment may not be longer than what corresponds to full-time doctoral education in four years' time. An employed doctoral student can, to a limited extent (maximum 20%), perform certain tasks within their role, e.g. training and administration. A new position as a doctoral student is for a maximum of one year, and then the employment may be renewed for a maximum of two years at a time.

As a doctoral student, you are entitled to a workplace with many employee benefits and monthly salary according to KTH's Doctoral student salary agreement . Read more about Doctoral studies (PhD) | KTH | Sweden.