Lund University, Faculty of Science, Department of Chemistry
Lund University was founded in 1666 and is repeatedly ranked among the world's
top 100 universities. The University has around 44 000 students and more than
8 000 staff based in Lund, Helsingborg and Malmö. We are united in our efforts
to understand, explain and improve our world and the human condition.
Lund University welcomes applicants with diverse backgrounds and experiences.
We regard gender equality and diversity as a strength and an asset.
We are looking for a PhD student in Machine Learning applied to life science
within WASP, placed at the department of biochemistry and structural biology.
The Wallenberg AI, Autonomous Systems and Software Program (WASP) is a major
national initiative for strategically motivated basic research, with the goal
of advancing Sweden into an internationally recognized and leading position in
the areas of artificial intelligence, autonomous systems and software.
The main focus of the research within WASP is artificial intelligence and
autonomous systems acting in collaboration with humans, adapting to and
learning from their environment through sensors, information and knowledge,
forming intelligent systems-of-systems. Read more at https: // wasp-sweden.org.
The WASP Graduate School is dedicated to provide the skills needed to analyze,
develop, and contribute to the interdisciplinary area of artificial
intelligence, autonomous systems and software. The curriculum provides the
foundations, perspectives, and state-of-the-art knowledge in the different
disciplines taught by leading researchers in the field. Read more at
https: // wasp-sweden.org/graduate-school.
The focus of the research is to develop machine learning methods to model and
design the three-dimensional structure of proteins. Deep learning approaches
(such as AlphaFold) has recently revolutionized protein structure
prediction, enabling highly accurate predictions of the atomic structures
based on amino acid sequence information. Similar advancements are expected
for the inverse problem, finding amino acid sequences that encode a desired
atomic structure. This is referred to as protein design and has many
applications in biomedicine, biotechnology and material science. The project
aims to develop deep generative models to design proteins that can
simultaneously adopt two conformations. Machine learning methods will be
combined with state-of-the-art approaches for computational protein design.
The main duties of doctoral students are to devote themselves to their
research studies which includes participating in research projects and third
cycle courses. The work duties can also include teaching and other
departmental duties (no more than 20%).
A person meets the general admission requirements for third-cycle courses and
study programmes if he or she:
has been awarded a second-cycle qualification, or
has satisfied the requirements for courses comprising at least 240 credits
of which at least 60 credits were awarded in the second cycle, or
has acquired substantially equivalent knowledge in some other way in
Sweden or abroad.
Very good oral and written proficiency in English.
The candidate should have an education background corresponding to a
master in a subject relevant to the PhD project, such as bioinformatics,
computational physics, physical or theoretical chemistry, applied
mathematics, statistics or computer science.
Sufficient educational background in mathematics/statistics to
successfully participate in the WASP research school.
A strong interest in applying machine learning methods to problems in
Selection for third-cycle studies is based on the student's potential to
profit from such studies. The assessment of potential is made primarily on the
basis of academic results from the first and second cycle. Special attention
is paid to the following:
Knowledge and skills relevant to the thesis project and the subject of study.
An assessment of ability to work independently and to formulate and tackle
research problems. Written and oral communication skills Other experience
relevant to the third-cycle studies, e.g. professional experience.
Other assessment criteria:
Strong background in mathematics and computer programming is highly
beneficial. Prior background in machine learning is advantageous. Experience
working with biological data (protein sequence and structure in particular)
is beneficial, but not required. Study background in chemistry and biology
Consideration will also be given to good collaborative skills, drive and
independence, and how the applicant, through his or her experience and skills,
is deemed to have the abilities necessary for successfully completing the
third cycle programme.
Terms of employment
Only those admitted to third cycle studies may be appointed to a doctoral
studentship. Doctoral studentships are regulated in the Higher Education
Ordinance (1993:100), chapter 5, 1-7 §§.
Instructions on how to apply
Applications shall be written in English and include a cover letter stating
the reasons why you are interested in the position and in what way the
research project corresponds to your interests and educational background. The
application must also contain a CV, degree certificate or equivalent, and
other documents you wish to be considered (grade transcripts, contact
information for your references, letters of recommendation, etc.).
Students with basic eligibility for third-cycle studies are those who- have
completed a second-cycle degree- have completed courses of at least 240
credits, of which at least 60 credits are from second-cycle courses, or- have
acquired largely equivalent knowledge in some other way, in Sweden or abroad.
The employment of doctoral students is regulated in the Swedish Code of
Statues 1998: 80. Only those who are or have been admitted to PhD-studies may
be appointed to doctoral studentships. When an appointment to a doctoral
studentship is made, the ability of the student to benefit from PhD-studies
shall primarily be taken into account. In addition to devoting themselves to
their studies, those appointed to doctoral studentships may be required to
work with educational tasks, research and administration, in accordance with
specific regulations in the ordinance.
Type of employment
Limit of tenure, four years according to HF 5 kap 7§.
The Faculty of Science conducts research and education within Biology,
Astronomy, Physics, Geosciences, Chemistry, Mathematics and Environmental
Science. The Faculty is organized into nine departments, gathered in the
northern campus area. The Faculty has approximately 1500 students, 330 PhD
students and 700 employees.
We kindly decline all sales and marketing contacts.
Type of employment Temporary position longer than 6 months
First day of employment Earliest 221001
Salary Monthly salary
Number of positions 1
Working hours 100
County Skåne län
Reference number PA2022/2314
Ingemar André, email@example.com, +46462224470
OFR/ST:Fackförbundet ST:s kansli, +46(0)46-2229362
SACO:Saco-s-rådet vid Lunds universitet , +46(0)46-2229364
SEKO: Seko Civil , +46(0)46-2229366
Last application date 14.Aug.2022 11:59 PM CEST
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